EPSRC Centre for New Mathematical Sciences Capabilities for Healthcare Technologies
Lead Research Organisation:
University of Liverpool
Department Name: Mathematical Sciences
Abstract
As quality of life constantly improves, the average lifespan will continue to increase. Underlining this improvement is the vast amount of the UK government's support to NHS (£133.5 billion in year 2011/12) and the UK pharmaceutical industry's R&D large investment (4.9 billion to R&D in year 2011/12). The expectation of quality healthcare is inevitably high from all stakeholders. Fortunately recent advances in science and technology have enabled us to work towards personalised medicine and preventative care. This approach calls for a collective effort of researchers from a vast spectrum of specialised subjects.
Advances in science and engineering is often accompanied by major development of mathematical sciences, as the latter underpin all other sciences. The UoL Centre will consist of a large and multidisciplinary team of applied and pure mathematicians, and statisticians together with healthcare researchers, clinicians and industrialists, collaborating with 15 HEIs and 40 NHS trusts plus other industrial partners and including our strongest groups:
MRC Centre in Drug Safety Science, Centre for Cell imaging (CCI for live 3D and 4D imaging), Centre for Mathematical Imaging Techniques (unique in UK), Liverpool Biomedical EM unit, MRC Regenerative Medicine Hub, NIHR Health Protection Research Units, MRC Hub for Trials Methodology Research.
Several research themes are highlighted below:
Firstly, an improved understanding of the interaction dynamics of cells and tissues is crucial to developing effective future cures for cancer. Much of the current work is in 2D, with restrictive assumptions and without access to real data for modelling. We shall use the unparalleled real data of cell interactions in a 3D setting, generated at UoL's CCI. The real-life images obtained will have low contrast and noise and they will be analysed and enhanced by our imaging team through developing accurate and high resolution imaging models. The main imaging tools needed are segmentation methods (identifying objects such as cells and tissues regions in terms of sizes, shapes and precise boundaries). We shall propose and study a class of new 3D models, using our imaging data and analysis tools, to investigate and predict the spatial-temporal dynamics.
Secondly, better models of how drugs are delivered to cells in tissues will improve personalised predictions of drug toxicity. We shall combine novel-imaging data of drug penetration into 3D experimental model systems with multi-scale mathematical models which scale-up from the level of cells to these model systems, with the ultimate aim of making better in-vitro to in-vivo predictions.
Thirdly, there exist many competing models and software for imaging processing. However, for real images that have noise and are of low contrast, few methods are robust and accurate. To improve the modelling, applied and pure mathematicians team up to consider using more sophisticated tools of hyperbolic geometry and Riemann surfaces and fractional calculus to meet the demand for accuracy, and, applied mathematicians and statisticians will team up to design better data fidelity terms to model image discrepancies.
Fourthly, resistance to current antibiotics means that previously treatable diseases are becoming deadly again. To understand and mitigate this, a better understanding is needed for how this resistance builds up across the human interaction networks and how it depends on antibiotic prescribing practices. To understand these scenarios, the mathematics competition in heterogeneous environments needs to be better understood. Our team links mathematical experts in analysing dynamical systems with experts in antimicrobial resistance and GPs to determine strategies that will mitigate or slow the development of anti-microbial resistance.
Our research themes are aligned with, and will add value to, existing and current UoL and Research Council strategic investments, activities and future plans.
Advances in science and engineering is often accompanied by major development of mathematical sciences, as the latter underpin all other sciences. The UoL Centre will consist of a large and multidisciplinary team of applied and pure mathematicians, and statisticians together with healthcare researchers, clinicians and industrialists, collaborating with 15 HEIs and 40 NHS trusts plus other industrial partners and including our strongest groups:
MRC Centre in Drug Safety Science, Centre for Cell imaging (CCI for live 3D and 4D imaging), Centre for Mathematical Imaging Techniques (unique in UK), Liverpool Biomedical EM unit, MRC Regenerative Medicine Hub, NIHR Health Protection Research Units, MRC Hub for Trials Methodology Research.
Several research themes are highlighted below:
Firstly, an improved understanding of the interaction dynamics of cells and tissues is crucial to developing effective future cures for cancer. Much of the current work is in 2D, with restrictive assumptions and without access to real data for modelling. We shall use the unparalleled real data of cell interactions in a 3D setting, generated at UoL's CCI. The real-life images obtained will have low contrast and noise and they will be analysed and enhanced by our imaging team through developing accurate and high resolution imaging models. The main imaging tools needed are segmentation methods (identifying objects such as cells and tissues regions in terms of sizes, shapes and precise boundaries). We shall propose and study a class of new 3D models, using our imaging data and analysis tools, to investigate and predict the spatial-temporal dynamics.
Secondly, better models of how drugs are delivered to cells in tissues will improve personalised predictions of drug toxicity. We shall combine novel-imaging data of drug penetration into 3D experimental model systems with multi-scale mathematical models which scale-up from the level of cells to these model systems, with the ultimate aim of making better in-vitro to in-vivo predictions.
Thirdly, there exist many competing models and software for imaging processing. However, for real images that have noise and are of low contrast, few methods are robust and accurate. To improve the modelling, applied and pure mathematicians team up to consider using more sophisticated tools of hyperbolic geometry and Riemann surfaces and fractional calculus to meet the demand for accuracy, and, applied mathematicians and statisticians will team up to design better data fidelity terms to model image discrepancies.
Fourthly, resistance to current antibiotics means that previously treatable diseases are becoming deadly again. To understand and mitigate this, a better understanding is needed for how this resistance builds up across the human interaction networks and how it depends on antibiotic prescribing practices. To understand these scenarios, the mathematics competition in heterogeneous environments needs to be better understood. Our team links mathematical experts in analysing dynamical systems with experts in antimicrobial resistance and GPs to determine strategies that will mitigate or slow the development of anti-microbial resistance.
Our research themes are aligned with, and will add value to, existing and current UoL and Research Council strategic investments, activities and future plans.
Planned Impact
Our team of applied, pure mathematicians and statisticians together with healthcare researchers, clinicians and industrialists will collaborate with 15 HEIs and 40 NHS trusts plus other industrial partners. Therefore the impact on the wide community is more pronounced and immediate than a responsive mode grant.
Academic impact. To the healthcare community, the proposed work will provide an insightful understanding of personalised medicine and preventative care. To the mathematical sciences community, the proposed work will advance several new directions in mathematics and statistics that will lead to high impact publications and high profile public addresses at major conferences. We see researchers in these communities as direct beneficiaries of the Centre.
The primary means of reaching out to users is by our User Engagement Forum via a series of Knowledge Exchange activities including visitor programmes; advisory service and maths and healthcare 'clinics'; summer schools; pump priming projects and activities to engage HEIs and industries; impact and public engagement activities; joint seminar series; workshops around specific problems. Some will be run with other EPSRC centres.
Economic Impact. The UK pharmaceutical industry in 2007 contributed £8.4 billion to the UK's GDP, investing 4.3 billion to R&D which is the third-highest share of global pharmaceutical R&D. The NHS budget for the UK was £133.5 billion in 2011/12 and medicines account for 10% of the NHS budget i.e. £13.4 billion. The Centre will make major contributions to UK R&D:
(i). Aided by image technologies, understanding the progression of the disease process is important to enable the industry target relevant biological processes. (ii). Incorporation of protein/cell level dynamics into tissues is necessary and essential to predict the overall toxicity. This study will lead to treatments optimised for specific patients. The pharmaceutical industry interests in drugs with less side-effects and stratified medicine. It will benefit from this Centre's new analysis tools and the UoL's MRC Centre in Drug Safety Science and MRC Regenerative Medicine Hub and Trials Hub in terms of extensive experimental data, computational simulations and scientific insights on tissues; therefore, we expect this impact to continue to be facilitated with our long-term collaborative partners and new parties to perform proof-of-principle trials.
Through existing and established connections, we would build further engagement including conversion of our results into commercial products.
Societal Impact. Cancer is due to uncontrolled growth and spread of abnormal cells. Our proposed work, aiming for better understanding of cells and tissues, is crucial to combat cancer. There were 14M new sufferers (8M deaths) with 338K in UK alone in 2012. Research impact is of massive scale.
With aging, plaque due to cholesterol, calcium, and fibrous tissue can build up in arteries and due to such, they can narrow and stiffen. Coronary angioplasty and stenting are to improve blood flow in the body's arteries and veins, with 75,000 procedures performed in England per year. Our study will optimise designs to minimise side effects. It will be conducted with clinicians. Benefit and publicity to NHS are immediate.
There is considerable concern in the society with common infectious diseases, which lead to 300M illnesses and more than 5M deaths each year worldwide with Ebola outbreak well-known and anti-microbial resistance posed as massive challenge. Finding a model for it by scaling up from small/local network information to large/global networks to understand diseases' network is of vital importance to Healthcare policy makers and service providers.
We will use these to engage the public at annual Science Festivals. We believe that these will not only raise awareness of the complexity in disease networks, but also generate interest in the community fascinated by bio-mimic system.
Academic impact. To the healthcare community, the proposed work will provide an insightful understanding of personalised medicine and preventative care. To the mathematical sciences community, the proposed work will advance several new directions in mathematics and statistics that will lead to high impact publications and high profile public addresses at major conferences. We see researchers in these communities as direct beneficiaries of the Centre.
The primary means of reaching out to users is by our User Engagement Forum via a series of Knowledge Exchange activities including visitor programmes; advisory service and maths and healthcare 'clinics'; summer schools; pump priming projects and activities to engage HEIs and industries; impact and public engagement activities; joint seminar series; workshops around specific problems. Some will be run with other EPSRC centres.
Economic Impact. The UK pharmaceutical industry in 2007 contributed £8.4 billion to the UK's GDP, investing 4.3 billion to R&D which is the third-highest share of global pharmaceutical R&D. The NHS budget for the UK was £133.5 billion in 2011/12 and medicines account for 10% of the NHS budget i.e. £13.4 billion. The Centre will make major contributions to UK R&D:
(i). Aided by image technologies, understanding the progression of the disease process is important to enable the industry target relevant biological processes. (ii). Incorporation of protein/cell level dynamics into tissues is necessary and essential to predict the overall toxicity. This study will lead to treatments optimised for specific patients. The pharmaceutical industry interests in drugs with less side-effects and stratified medicine. It will benefit from this Centre's new analysis tools and the UoL's MRC Centre in Drug Safety Science and MRC Regenerative Medicine Hub and Trials Hub in terms of extensive experimental data, computational simulations and scientific insights on tissues; therefore, we expect this impact to continue to be facilitated with our long-term collaborative partners and new parties to perform proof-of-principle trials.
Through existing and established connections, we would build further engagement including conversion of our results into commercial products.
Societal Impact. Cancer is due to uncontrolled growth and spread of abnormal cells. Our proposed work, aiming for better understanding of cells and tissues, is crucial to combat cancer. There were 14M new sufferers (8M deaths) with 338K in UK alone in 2012. Research impact is of massive scale.
With aging, plaque due to cholesterol, calcium, and fibrous tissue can build up in arteries and due to such, they can narrow and stiffen. Coronary angioplasty and stenting are to improve blood flow in the body's arteries and veins, with 75,000 procedures performed in England per year. Our study will optimise designs to minimise side effects. It will be conducted with clinicians. Benefit and publicity to NHS are immediate.
There is considerable concern in the society with common infectious diseases, which lead to 300M illnesses and more than 5M deaths each year worldwide with Ebola outbreak well-known and anti-microbial resistance posed as massive challenge. Finding a model for it by scaling up from small/local network information to large/global networks to understand diseases' network is of vital importance to Healthcare policy makers and service providers.
We will use these to engage the public at annual Science Festivals. We believe that these will not only raise awareness of the complexity in disease networks, but also generate interest in the community fascinated by bio-mimic system.
Organisations
- University of Liverpool (Lead Research Organisation, Project Partner)
- Beihang University (Collaboration)
- Wenzhou Medical University (Collaboration)
- Massachusetts Eye and Ear Infirmary (Collaboration)
- ROYAL LIVERPOOL AND BROADGREEN UNIVERSITY HOSPITALS NHS TRUST (Collaboration)
- Implandata Ophthalmic Products GmbH (Collaboration)
- THE WALTON CENTRE (Collaboration)
- UNIVERSITY OF LIVERPOOL (Collaboration)
- GlaxoSmithKline (GSK) (Collaboration)
- Nanoflex (Collaboration)
- World Health Organization (WHO) (Collaboration)
- Royal Liverpool University Hospital (Collaboration)
- Mirada Medical Ltd (Collaboration)
- PUBLIC HEALTH ENGLAND (Collaboration)
- Lancaster University (Collaboration)
- British Heart Foundation (BHF) (Collaboration)
- University of Sussex (Collaboration)
- City, University of London (Collaboration)
- UNIVERSITY OF GLASGOW (Collaboration)
- Walton Centre (Project Partner)
- Liverpool Heart and Chest Hospital NHS Trust (Project Partner)
- North West Coast Academic Health Sci Nwk (Project Partner)
- Mirada Medical (United Kingdom) (Project Partner)
- Public Health England (Project Partner)
- Dudley Group NHS Foundation Trust (Project Partner)
- Liverpool Health Partners (Project Partner)
- Bionow Ltd (Project Partner)
- Unilever (United Kingdom) (Project Partner)
- Clatterbridge Cancer Ctr NHS Fdn Trust (Project Partner)
- Durham University (Project Partner)
- University of Salford (Project Partner)
- Carl Zeiss (United Kingdom) (Project Partner)
- AstraZeneca (United States) (Project Partner)
- University of Edinburgh (Project Partner)
- University of Liverpool (Project Partner)
- Liverpool Women's Hospital (Project Partner)
Publications
Kolamunnage-Dona R
(2021)
Sorafenib is associated with a reduced rate of tumour growth and liver function deterioration in HCV-induced hepatocellular carcinoma.
in Journal of hepatology
Kumar S
(2018)
Who interacts with whom? Social mixing insights from a rural population in India.
in PloS one
Kwok KO
(2018)
Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents.
in Journal of the Royal Society, Interface
Kwok KO
(2018)
A systematic review of transmission dynamic studies of methicillin-resistant Staphylococcus aureus in non-hospital residential facilities.
in BMC infectious diseases
Kyffin JA
(2019)
Characterisation of a functional rat hepatocyte spheroid model.
in Toxicology in vitro : an international journal published in association with BIBRA
Kyffin JA
(2019)
Preparation of Primary Rat Hepatocyte Spheroids Utilizing the Liquid-Overlay Technique.
in Current protocols in toxicology
Kyffin JA
(2018)
Impact of cell types and culture methods on the functionality of in vitro liver systems - A review of cell systems for hepatotoxicity assessment.
in Toxicology in vitro : an international journal published in association with BIBRA
Labeur T
(2019)
Improved survival prediction and comparison of prognostic models for patients with hepatocellular carcinoma treated with sorafenib
in Liver International
Labeur TA
(2020)
Response to: Prognostication of HCC patients under sorafenib is not always possible.
in Liver international : official journal of the International Association for the Study of the Liver
Leedale J
(2018)
A Combined In Vitro/In Silico Approach to Identifying Off-Target Receptor Toxicity.
in iScience
Title | collaboration with music composer Emily and launch of PRISM |
Description | PRiSM is the RNCM Centre for Practice & Research in Science & Music PRiSM brings together a number of creative collaborations between the sciences and music. PRisM was launched the 04/10/2017 with "The Music of Proof" performance |
Type Of Art | Performance (Music, Dance, Drama, etc) |
Year Produced | 2017 |
Impact | Dr Howard music composition has been influenced by discussion with mathematicians and biologists |
URL | https://www.rncm.ac.uk/research/research-centres-rncm/prism/ |
Description | The project has successfully finished in 2021, and the completed projects have 1. T1 Project 1 (stenting). We have found a relationship between stents' size and damage to the stents in operating conditions. This is through constructive description of favourable and unfavourable conditions for endovascular sealing of abdominal aortic aneurysms and by our analysis tool developed at LCMH. The finding is published in Proceedings of the Royal Society and the Nature Sci Report. 2. T2 Project 1 (segmentation using partial priors). We have designed reliable minimal path-following algorithms to produce an accurate segmentation which is much faster than the usual fully 3D models. The speed-up is from dimension reduction while the reliability is by achieving non-intersecting paths. We have come up with a new method to reduce the number of parameters in a model and also a new way to define distances to localize an object more precisely than any other work before. 3. T2 Project 2 (multi-modality image co-registration). We have found new models for aligning images which are much better than the established models based on normalized gradients or mutual information. We are proud to have found fundamental modifications to previous models so that 1 few % of improvements are achieved without much effort and we also managed to apply game theory to registration models with which we can reduce the number of coupling parameters. The implication of the latter to deep learning is currently explored. 4. A new eco-evolutionary framework for constructing evolutionary mathematical models with network structure was developed. 5. T3 Our work modelling the development of AMR in cystic fibrosis patients is enabling us to gain insights into potentially better antibiotic treatment courses to minimise the development of AMR. 6. T3 Work on modelling influenza dynamics in the UK with an age-structured population using an MCMC model enables prediction of transmission and immunity parameters from known birth/death and migration patterns. It explains the observation of severe epidemics of A/H3N2 occurring every 6-7 years. 7. T1 Multiscale work. We have developed a multiscale mathematical modelling framework to describe the temporal and spatial dynamics of drugs in multicellular environments. The model combines information relating to the diffusion, transport and metabolism of chemical species (drugs) in 2D and 3D environments. The framework allows for the study of different transport mechanisms by varying boundary conditions on the cell membrane and for the study of the effects of cellular arrangement and physicochemical properties on the transport and penetration of drugs to simulate the problem for in vitro microtissue environments. |
Exploitation Route | Through our projects partners and new collaborators, as well as engagement activities. They participate the projects directly. We run regular networking events to engage national and international collaborators. Several new partners who can make use of findings have been identified and implementations on new data are in progress. We have also organised joint workshops with other EPSRC Centres. Outcomes of this funding have also led to several new collborations for follow-up works. The modelling framework from multiscale modelling will be used by academic researchers and industry who use micro-tissue in vitro models for testing drug efficacy and toxicity. Whilst the model was initially used to study hepatocyte spheroids, it has a wider range of applications, and we are collaborating with the Institute of Cancer Research to look at its utility in the development of cancer treatments. The new imaging models are being applied to a wider class of data from new partners such as Nottingham (pancreatic caners), the Walton Center (brain tumours), another department of Astra-Zeneza (preclinical imaging), GSK and Clatterbridge Cancer Centre. New grants have been secured for sustainable development in the Centre and a few more new and emerging Maths-Healthcare problems (such as cancer, pathology, brains) are identified with further collaborators on aboard. |
Sectors | Communities and Social Services/Policy Digital/Communication/Information Technologies (including Software) Healthcare Manufacturing including Industrial Biotechology Pharmaceuticals and Medical Biotechnology |
URL | http://tinyurl.com/EPSRC-LCMH |
Description | The Centre aims to tackle healthcare challenges proposed by clinicians and industrialists by novel mathematics. Thus each started project (9 initially and then expanded with new funding) has aimed for direct impact to healthcare sector. All completed projects (eg Theme 1 P1, Theme P1 and Theme 3 P1) have made big impacts, specifically (1) the Stenting project (Theme 1 Project 1) has produced results that have been used by clinicians to decide when the studied procedure is suitable for a patient before operations; this facilitates selection of stents and is done a rigorously way. The follow-up work is to extend the results to other stents which are not part of the original proposal. (2) the Interactive Segmentation project (Theme 2 Project 1) has also produced impressive results (as with directly industrial involvement) and the collaborating partner will start formal validation process this year to aim for adoption into products. Our work has a potential to impact future NHS diagnostic tools and platforms from which we take pride. In fact, we have started several routes of applying to specific types of segmentation problems including on-going work with IAL group (London) and the Walton Centre. Through new partnerships, we have identified companies who are willing to assess our new models for their products which are being pursued. The work is used by the Walton Centre and Royal Liverpool Hospital. It has led to new follow-up projects with Astra-Zeneca which are on-going. (3) the influenza project (Theme 3 Project 1) is developing National scale population models of influenza sub-type transmission, infection and immunity. World Health Organization data will be used to infer key parameter values pertaining to antigenic drift rates and subtype transmission and interactions. A workshop was conducted in summer 2017 to engage with policy makers and other stakeholders. This has led to new grants and works with WHO to make use of more data to improve prediction accuracy. The unwelcoming covid pandemic has interrupted face to face meetings with visitors. However we had benefited with increased interests in new pump-priming type engagements which have led us to new partners and more impacts in UK and beyond. |
Sector | Digital/Communication/Information Technologies (including Software),Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
Impact Types | Societal Economic Policy & public services |
Description | Improvement of clinical Practice -- Project 1 |
Geographic Reach | Europe |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | Our results have triggered an instant review of the procedures in selecting typs of sents to use and the conclusion of stopping the EVAS (Endovascular aneurysm sealing system) procedure for old patients who are at higher risk. Refer to the report of https://news.liverpool.ac.uk/2018/04/09/mathematicians-devise-new-model-to-study-response-of-endovascular-aneurysm-sealing/ and see the article 'Deformation and dynamic response of abdominal aortic aneurysm sealing' is published in Nature Scientific Reports: https://www.nature.com/articles/s41598-017-17759-3 [Scientific Reports volume 7, Article number: 17712 (2017)] |
Description | (EvoGamesPlus) - Evolutionary games and population dynamics: from theory to applications |
Amount | € 3,980,390 (EUR) |
Funding ID | 955708 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 03/2021 |
End | 02/2025 |
Description | (RenalToolBox) - Developing novel tools and technologies to assess the safety and efficacy of cell-based regenerative medicine therapies, focusing on kidney disease |
Amount | € 4,071,175 (EUR) |
Funding ID | 813839 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 11/2018 |
End | 10/2022 |
Description | (TREGeneration) - Repair of tissue and organ damage in refractory chronic graft versus host disease after hematopoietic stem cell transplantation by the infusion of purified allogeneic donor regulatory T lymphocytes |
Amount | € 5,899,250 (EUR) |
Funding ID | 643776 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 01/2015 |
End | 12/2019 |
Description | 3DBioNet: an integrated technological platform for 3D micro-tissues |
Amount | £626,046 (GBP) |
Funding ID | MR/R025762/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2018 |
End | 02/2022 |
Description | A Dragonfly multimodal fast imaging platform with SRRF-stream (Super-Resolution Radial Fluctuation) in the Liverpool Centre for Cell Imaging (CCI) |
Amount | £450,000 (GBP) |
Funding ID | BB/R01390X/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 04/2018 |
End | 04/2019 |
Description | ARTFUL Statement of Need (SoN) for a mid range facility (MRF) |
Amount | £507,705 (GBP) |
Funding ID | EP/R007926/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2017 |
End | 04/2022 |
Description | Brain architecture and connectivity at epilepsy diagnosis: markers of cognitive dysfunction and pharmacoresistance |
Amount | £778,719 (GBP) |
Funding ID | MR/S00355X/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 04/2019 |
End | 04/2024 |
Description | Brain architecture and fuction at epilepsy diagnosis: markers of pharmacoresistance and cognitive dysfunction |
Amount | £645,980 (GBP) |
Funding ID | MR/S00355X/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start |
Description | Cancer Research Uk Early Detection Committee - Project Award |
Amount | £430,601 (GBP) |
Funding ID | C7738/A26196 |
Organisation | Cancer Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 06/2018 |
End | 06/2021 |
Description | Clinical and technical validation of infrared absorbance spectra to predict malignant transformation in oral potentially malignant disorders (OPMDs) |
Amount | £407,638 (GBP) |
Funding ID | EDDPJT-May23/100024 |
Organisation | Cancer Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2023 |
End | 09/2026 |
Description | Deep Learning Ultra Low-Frequency Heart Rate Variability from raw ECG |
Amount | £229,820 (GBP) |
Funding ID | BB/S008136/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2019 |
End | 03/2023 |
Description | Defining drug delivery into and across the oral mucosa using a tissue engineering and mathematical modelling approach |
Amount | £430,354 (GBP) |
Funding ID | NC/W001160/1 |
Organisation | National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) |
Sector | Public |
Country | United Kingdom |
Start | 12/2021 |
End | 03/2024 |
Description | Developing novel tools and technologies to assess the safety and efficacy of cell-based regenerative medicine therapies, focusing on kidney disease RenalToolBox |
Amount | £808,530 (GBP) |
Funding ID | 813839 |
Organisation | Marie Sklodowska-Curie Actions |
Sector | Charity/Non Profit |
Country | Global |
Start |
Description | Development of New Low Cost Point of Care Diagnostic Technologies for Diabetic Retinopathy in China |
Amount | £1,150,450 (GBP) |
Funding ID | EP/R014094/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 02/2018 |
End | 01/2022 |
Description | Developments of new sensor technology in collaboration with TRITEC Developments Ltd to obtain better sensor technology for the work at Alder Hey Hospital |
Amount | £11,000 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start |
Description | Drivers of Resistance in Uganda and Malawi: The DRUM Consortium |
Amount | £3,000,000 (GBP) |
Funding ID | MR/S004793/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start |
Description | EPSRC - iCASE studentship (Smith Institute) |
Amount | £86,000 (GBP) |
Funding ID | EPSRC Voucher 17000203 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2017 |
End | 09/2021 |
Description | EPSRC First Grant Scheme (Dr T Valkonen) Centre New lecturer |
Amount | £168,000 (GBP) |
Funding ID | EP/P021298/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2017 |
End | 03/2019 |
Description | Impact of network-structured populations on evolution. |
Amount | £568,000 (GBP) |
Funding ID | EP/T031727/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 02/2021 |
End | 02/2024 |
Description | Investigating the potential of cell-based regenerative medicine therapies to ameliorate acute kidney injury and prevent progression to chronic disease |
Amount | £40,000 (GBP) |
Funding ID | JFS_IN_001_20170914 |
Organisation | Kidney Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 04/2019 |
Description | MRC Skills Development Fellowships |
Amount | £2,000,000 (GBP) |
Funding ID | SDF/Williamson |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 11/2017 |
End | 12/2020 |
Description | Neurodevelopment after prenatal exposure to seizures (NAPES) Study |
Amount | £149,963 (GBP) |
Funding ID | P1703 |
Organisation | Epilepsy Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2018 |
End | 02/2021 |
Description | Newton Research Collaboration Programme Award |
Amount | £16,660 (GBP) |
Funding ID | NW/CHEN |
Organisation | Royal Academy of Engineering |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2017 |
End | 03/2018 |
Description | Pilot Study: Alder Hey Childrens Hospital |
Amount | £347,992 (GBP) |
Funding ID | EP/P016774/1 |
Organisation | University of Exeter |
Sector | Academic/University |
Country | United Kingdom |
Start | 01/2017 |
End | 03/2019 |
Description | Plasma Biomarkers for Diagnosis of Lung Cancer |
Amount | £36,900 (GBP) |
Organisation | F. Hoffmann-La Roche AG |
Department | Roche Diagnostics |
Sector | Private |
Country | Global |
Start | 12/2019 |
End | 05/2020 |
Description | Quantification of uncertainty within systems pharmacology to optimise personalised therapy |
Amount | £236,135 (GBP) |
Funding ID | MR/S019332/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2019 |
End | 12/2021 |
Description | Shape, shear, search & strife; mathematical models of bacteria |
Amount | £361,729 (GBP) |
Funding ID | EP/S033211/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2020 |
End | 08/2023 |
Description | Shape, shear, search & strife; mathematical models of bacteria |
Amount | £340,000 (GBP) |
Funding ID | EP/S033211/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2019 |
End | 08/2022 |
Description | The regulation of collagen (I) homotrimer synthesis and its role in musculoskeletal dysfunction |
Amount | £557,967 (GBP) |
Funding ID | MR/R00319X/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2017 |
End | 11/2020 |
Description | Volatile OrganIc compounDs in Bladder Cancer (VOID Bladder Cancer) |
Amount | £171,906 (GBP) |
Funding ID | 21068 |
Organisation | Cancer Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2017 |
End | 12/2019 |
Description | Volatile organic compounds for the detection of colorectal cancer (VODECA) |
Amount | £440,840 (GBP) |
Organisation | Cancer Research UK |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start |
Title | Segmentation and monitoring of stents |
Description | Our imaging work has led to new collaborations with the Royal Liverpool Hospital on segmentation and monitoring of stents. Since the first successul triails in 2014, further work (2016-2020) has incoporated imporved AI techniques and the new tool is used by the hospital. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | The results are published in open literature. A latest paper has been submitted to Nature Sci Reports (2022). |
Title | Case data with referenced sources for cities within China from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Case_data_with_referenced_sources_for_cities_within_China_f... |
Title | Case data with referenced sources for cities within China from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Case_data_with_referenced_sources_for_cities_within_China_f... |
Title | Case data with referenced sources for other countries/regions from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Case_data_with_referenced_sources_for_other_countries_regio... |
Title | Case data with referenced sources for other countries/regions from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Case_data_with_referenced_sources_for_other_countries_regio... |
Title | Dataset from Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents |
Description | Dataset |
Type Of Material | Database/Collection of data |
Year Produced | 2018 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Dataset_from_Temporal_variation_of_human_encounters_and_the... |
Title | Dataset from Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents. |
Description | Dataset |
Type Of Material | Database/Collection of data |
Year Produced | 2018 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Dataset_from_Temporal_variation_of_human_encounters_and_the... |
Title | Dataset from Temporal variation of human encounters and the number of locations in which they occur: a longitudinal study of Hong Kong residents. |
Description | Dataset |
Type Of Material | Database/Collection of data |
Year Produced | 2018 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/Dataset_from_Temporal_variation_of_human_encounters_and_the... |
Title | R code file sourced by figures_main_paper.R from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/R_code_file_sourced_by_figures_main_paper_R_from_Novel_coro... |
Title | R code file sourced by figures_main_paper.R from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/R_code_file_sourced_by_figures_main_paper_R_from_Novel_coro... |
Title | R code for generating Figures 2, 3 and 4 and Table 1 and numbers used in main text. from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/R_code_for_generating_Figures_2_3_and_4_and_Table_1_and_num... |
Title | R code for generating Figures 2, 3 and 4 and Table 1 and numbers used in main text. from Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates |
Description | Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information.This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/dataset/R_code_for_generating_Figures_2_3_and_4_and_Table_1_and_num... |
Title | circ_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | circ_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | circ_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | circ_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | circ_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | circ_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | circ_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | circ_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | circ_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | circ_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | circ_pg_coopE_rough_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N20_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N20_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N30_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N30_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N40_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N40_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N50_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_N50_csv_from_The_effect_of_network_topology_on_... |
Title | circ_pg_coopE_rough_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_T05_N50_csv_from_The_effect_of_network_topology... |
Title | circ_pg_coopE_rough_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_T05_N50_csv_from_The_effect_of_network_topology... |
Title | circ_pg_coopE_rough_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_T25_N50_csv_from_The_effect_of_network_topology... |
Title | circ_pg_coopE_rough_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_coopE_rough_T25_N50_csv_from_The_effect_of_network_topology... |
Title | circ_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | circ_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | circ_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circ_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circ_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circpg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | circpg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | circpg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circpg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circpg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_m_from_The_effect_of_network_topology_on_optimal_explorati... |
Title | circpg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_m_from_The_effect_of_network_topology_on_optimal_explorati... |
Title | circpg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | circpg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | circpg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_m_from_The_effect_of_network_topology_on_optimal_expl... |
Title | circpg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_m_from_The_effect_of_network_topology_on_optimal_expl... |
Title | circpg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | circpg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circpg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | circpg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_e... |
Title | circpg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_e... |
Title | circpg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | circpg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | circpg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | circpg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg_bc50_m_from_The_effect_of_network_topology_on_optimal_explor... |
Title | circpg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/circpg_bc50_m_from_The_effect_of_network_topology_on_optimal_explor... |
Title | comp_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | comp_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | comp_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | comp_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | comp_pg_bc_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_fine_N50_csv_from_The_effect_of_network_topology_o... |
Title | comp_pg_bc_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_fine_N50_csv_from_The_effect_of_network_topology_o... |
Title | comp_pg_bc_coopE_rough_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_rough_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_bc_coopE_rough_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_rough_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | comp_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | comp_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | comp_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | comp_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | comp_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | comp_pg_coopE_rough_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N10_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N10_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N20_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N20_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N30_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N30_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N40_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N40_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N50_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_N50_csv_from_The_effect_of_network_topology_on_... |
Title | comp_pg_coopE_rough_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T05_N10_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T05_N10_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T05_N50_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T05_N50_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T25_N10_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T25_N10_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T25_N50_csv_from_The_effect_of_network_topology... |
Title | comp_pg_coopE_rough_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_coopE_rough_T25_N50_csv_from_The_effect_of_network_topology... |
Title | comp_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | comp_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | comp_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | comp_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/comp_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | compg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | compg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | compg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | compg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_m_from_The_effect_of_network_topology_on_optimal_exploratio... |
Title | compg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_m_from_The_effect_of_network_topology_on_optimal_exploratio... |
Title | compg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | compg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | compg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_m_from_The_effect_of_network_topology_on_optimal_explo... |
Title | compg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_m_from_The_effect_of_network_topology_on_optimal_explo... |
Title | compg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_m_from_The_effect_of_network_topology_on_optimal_explo... |
Title | compg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_m_from_The_effect_of_network_topology_on_optimal_explo... |
Title | compg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | compg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | compg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | compg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_ex... |
Title | compg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_ex... |
Title | compg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_ex... |
Title | compg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_ex... |
Title | compg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_opt... |
Title | compg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optima... |
Title | compg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_op... |
Title | compg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg_bc50_m_from_The_effect_of_network_topology_on_optimal_explora... |
Title | compg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/compg_bc50_m_from_The_effect_of_network_topology_on_optimal_explora... |
Title | star_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | star_pg_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_cfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | star_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | star_pg_bc_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_fine_N10_csv_from_The_effect_of_network_topology_o... |
Title | star_pg_bc_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_fine_N50_csv_from_The_effect_of_network_topology_o... |
Title | star_pg_bc_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_fine_N50_csv_from_The_effect_of_network_topology_o... |
Title | star_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_bc_coopE_rough_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_coopE_rough_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | star_pg_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_bc_dfix_csv_from_The_effect_of_network_topology_on_optimal_... |
Title | star_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | star_pg_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | star_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_cfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N10_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N20.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N20_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N30.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N30_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N40.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N40_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_N50_csv_from_The_effect_of_network_topology_on_o... |
Title | star_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T05_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T05_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T05_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N10.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N10_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_coopE_fine_T25_N50.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_coopE_fine_T25_N50_csv_from_The_effect_of_network_topology_... |
Title | star_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | star_pg_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_csv_from_The_effect_of_network_topology_on_optimal_exp... |
Title | star_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_T05_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | star_pg_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/star_pg_dfix_T25_csv_from_The_effect_of_network_topology_on_optimal... |
Title | starpg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | starpg10_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | starpg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg10_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg10_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | starpg10_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | starpg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg10_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg10_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg10_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg10_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg10_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg10_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_m_from_The_effect_of_network_topology_on_optimal_explorati... |
Title | starpg50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_m_from_The_effect_of_network_topology_on_optimal_explorati... |
Title | starpg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | starpg50_fast.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_csv_from_The_effect_of_network_topology_on_optimal_ex... |
Title | starpg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_m_from_The_effect_of_network_topology_on_optimal_expl... |
Title | starpg50_fast.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_m_from_The_effect_of_network_topology_on_optimal_expl... |
Title | starpg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg50_fast_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_T05_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg50_fast_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_T25_csv_from_The_effect_of_network_topology_on_optima... |
Title | starpg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | starpg50_fast_bc.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_csv_from_The_effect_of_network_topology_on_optimal... |
Title | starpg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_e... |
Title | starpg50_fast_bc.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_m_from_The_effect_of_network_topology_on_optimal_e... |
Title | starpg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg50_fast_bc_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_cfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg50_fast_bc_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_bc_dfix_csv_from_The_effect_of_network_topology_on_op... |
Title | starpg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg50_fast_cfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_cfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_cfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_cfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_csv_from_The_effect_of_network_topology_on_optim... |
Title | starpg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_dfix_T05.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_T05_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg50_fast_dfix_T25.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg50_fast_dfix_T25_csv_from_The_effect_of_network_topology_on_o... |
Title | starpg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg_bc50_m_from_The_effect_of_network_topology_on_optimal_explor... |
Title | starpg_bc50.m from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population |
Description | We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://rs.figshare.com/articles/starpg_bc50_m_from_The_effect_of_network_topology_on_optimal_explor... |
Description | Beihang |
Organisation | Beihang University |
Country | China |
Sector | Academic/University |
PI Contribution | Introduction of biomechanics skills into the biomedical research carried out at Beihang |
Collaborator Contribution | Funding and applications of biomedical research |
Impact | we are collaborating on a number of papers, none of them have been published yet. |
Start Year | 2018 |
Description | Collaboration with Public Health England |
Organisation | Public Health England |
Country | United Kingdom |
Sector | Public |
PI Contribution | Scoping work to identify research questions of direct relevance to PHE regarding influenza evolution and transmission within the UK. |
Collaborator Contribution | Provided time for meetings |
Impact | Paper submitted: "Using propensity score estimation in an adjusted study design for estimating indirect and direct vaccine effectiveness in observation studies, with application to rotavirus vaccination". Multi-disciplinary (epidemiology, mathematics, socio-demographic modelling, medicine). |
Start Year | 2016 |
Description | Dr Hermanowicz (GlaxoSmithKline London) |
Organisation | GlaxoSmithKline (GSK) |
Country | Global |
Sector | Private |
PI Contribution | Theme 2: Professor Ke Chen and Dr Anis Theljani are working with Dr Hermanowicz (GlaxoSmithKline London) in some challenging multimodality registration problems (Optic-MRI). We have regular collaborative meetings with GSK. Our methods have been tested with GSK data and initial results are encouraging. These will form the basis for future funding applications and direct GSK funding. |
Collaborator Contribution | GSK have provided us with data in order to test our methods. They also attend regular collaborative meetings. |
Impact | Our methods have been tested with GSK data and initial results are encouraging. These will form the basis for future funding applications and direct GSK funding. No impact recorded yet. |
Start Year | 2018 |
Description | Implandata |
Organisation | Implandata Ophthalmic Products GmbH |
Country | Germany |
Sector | Private |
PI Contribution | This is a collaboration in the development of an intraocular pressure measurement device developed by Implandata, which is to be tested and validated by our group. |
Collaborator Contribution | The partner will cover the cost of the testing and validation study. |
Impact | Not yet. After the validation work is completed, publications will be produced. There may also be further collaboration in device refinement. |
Start Year | 2019 |
Description | Pump Priming - Advanced signal processing for personalised portable EEG |
Organisation | University of Liverpool |
Department | Department of Electrical Engineering and Electronics |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | The project was a feasibility study to test the implementation of flexible signal processing algorithms to allow possible personalisation of wearable electroencephalogram (EEG) systems. The proposed approach was tested on a state-of-the-art, but relatively cheap, commercial EEG device (Neuroelectrics Enobio 8), which allows real-time data stream to external software. The project involved a collaboration with clinicians at Alder Hey hospital, to get feedback on the medical interpretation of signals, and with a UK-based manufacturer of wearable EEG, to get feedback on the software implementation from a manufacturer's point of view. Tests involving EEG measurements were carried out on the PI only. |
Collaborator Contribution | As above |
Impact | The technical outcome of the project was a preliminary software interface to stream EEG data from the commercial EEG system to an external software, which was designed in a flexible way to allow an easy customisation of signal processing algorithms. Beside the technical aspects, however, the project had an extremely positive outcome in terms of networking. The PI established a very fruitful collaboration with a team of neurologists and neurophysiologists at Alder Hey hospital, which led to follow-on research activities. This collaboration has already been successful in securing two PhD studentships, a collaborative grant (Hugh Greenwood Legacy Fund) and a Knowledge Exchange & Impact Voucher. |
Start Year | 2017 |
Description | Pump Priming - Developments of novel imaging methods for cell collisions |
Organisation | University of Sussex |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Cell tracking is becoming increasingly important in cell biology as it provides a valuable tool for analysing experimental data and hence furthering our understanding of dynamic cellular phenomena. The advent of high-throughput, high-resolution microscopy and imaging techniques means that a wealth of large data is routinely generated in many laboratories. Due to the sheer magnitude of the data involved manual tracking is often cumbersome and the development of computer algorithms for automated cell tracking is thus highly desirable. On the other hand, real world data is noisy and unstructured. To fully automate cell tracking is challenging. A wide recognised topic arises when cells collide together (during migration). Failing to correctly categorise this event will result in false terminations of cell tracks. This not only creates inaccuracy but also the prolonged effects will negatively affect detections on other important events such as proliferation. There have been some researches trying to solve this problem, for example, Bensch and Ronneberger proposed a segmentation technique in 2015 to accurately identify cell outlines in phase contrast images. However, like many other theoretical researches, they lack of practicality and would require a number of adaptations and robust implementation in order to be effective to real world data. The proposed collaboration with LCMH is to come up with a clear, practical idea to deal with cell collisions, that can be applied to real world datasets with minimal assumptions and limitations. It is also my intention to collaborate with members of LCMH, testing and improving the cell tracking functionality of tools used by LCMH. |
Collaborator Contribution | As above |
Impact | Ongoing - no outcomes reported yet. |
Start Year | 2018 |
Description | Pump Priming - Modelling insulin effects on cell cycle and bio-energetics |
Organisation | University of Liverpool |
Department | School of Biological Sciences Liverpool |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | This will be an interdisciplinary effort to gain greater insight into the effect of insulin on cell cycle and bioenergetics. At present, there is no understanding of how the different pathways downstream insulin control proliferation and the balance between aerobic and anaerobic energy production. We need to define a conceptual integration of the mechanisms regulating proliferation and use of energy in a wide range of cell types. We plan to achieve this with a workshop with leading biology expert (Prof. Stefano Biffo) and clinicians (Prof. Josep Roca and Dr. Michael Trenell). The novelty will be in the integration between the eIF6, mTOR and MEK pathways and their linkage to cell-cycle control, building on knowledge acquired in (1,2,3). Special focus will be given to information that can be gained from single cell data (rather than population averages) and incorporation of this information into the models. (1) Clarke et al., (2017), Cell Rep.; (2) Brina et al., (2015), Nature Communications; (3) Ankers, Basili, Pisconti, Bearon and Falciani, A systems biology approach identifies mTOR-independent and dependent relationships between insulin and the cell cycle in muscle progenitors, in prep. |
Collaborator Contribution | As above |
Impact | Ongoing - no output yet recorded. |
Start Year | 2018 |
Description | Pump Priming - Music and mathematics interrogate brain tumour dissemination |
Organisation | University of Liverpool |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | AIMS - Two connected parts: (1)To use mathematics to interrogate brain tumour dissemination & thus improve chemotherapy treatment protocols. (2)To develop the collaboration between EH and the Dept. of Mathematical Sciences through an investigation of a project at an interface of maths, music & health. |
Collaborator Contribution | As above |
Impact | OUTCOMES - (1) Presentation (RB) at LCMH event, Liverpool, Sep 2017 (2) Allocation of department GTA studentship to Marianne Scott (MS) to work on cell motility (3) MSc dissertation (distinction) (MS/RB) "The Persistent Random Walk Model and its application to Glioblastoma cell migration" (4) Video presentation at PRiSM launch, Manchester, Oct 2017 (5) Poster presentation at Liverpool-Glasgow centre meeting (Marianne Scott, RB), Liverpool, Aug 2018 (6) Private premiere of 'Outlier' for solo viola (EH), London, Sep 2018 (7) R. Richards, D. Mason, R. Levy, R. Bearon & V. See, "4D imaging and analysis of multicellular tumour spheroid cell migration and invasion" Publication in preparation (RB provided revisions to final draft in Sep 2018). (8) Invitation to Oaxaca BIRS-CMO workshop, "Mathematical Challenges in the Analysis of Continuum Models for Cancer Growth, Evolution and Therapy" (RB), November 2018 |
Start Year | 2017 |
Description | Pump Priming - New Development of AI Techniques for Heart Imaging |
Organisation | University of Glasgow |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Cardiovascular magnetic resonance imaging (CMR) has established itself as the non-invasive gold standard for assessing cardiac function (volume and strain) for a wide range of cardiovascular diseases, and it is also widely used in the mathematical modelling communities for developing personalised medicine. However, the geometry of the heart used in mathematical modelling currently is acquired by manual delineation of CMR images, which is time-consuming, tedious and error-prone. There is an urgent need to develop a framework to automatically analyse CMR image at all time points across a cardiac cycle, derive clinical measures in real time, and feed to subsequent mathematical modelling. This will facilitate large-population studies, such as the UK Biobank (http://ukbiobank.ac.uk). Artificial intelligence (AI) algorithms, especially deep convolutional neural networks, have demonstrated great potential in a number of visual tasks including objective recognition not only in natural images, but also in CMR images [Vigneault et al, 2018; Bai et al, 2018]. This pump-priming project is planned to start on 1 Oct 2018 for 6 months. The overarching aim of this project is to obtain preliminary data for the forthcoming programme grant application. Our specific objectives are as follows. Sub-project 1: AI-based Automatic Segmentation of Ventricular Border 1. Optimise existing AI segmentation techniques for the segmentation of heart CMR data. 2. Investigate new activation/cost functions and optimisation methods for AI. 3. Evaluate the performance of the new AI tools for ventricular border segmentation with the Glasgow team. Sub-project 2: Variational approach for longitudinal strain estimation 1. Develop new regularization/cost function and optimisation method for AI based registration, and evaluate the accuracy and reliability with ground truth data provided by the Glasgow team. 2. Evaluate the performance of the new approaches on a large cohort of MI patient segmentation with the Glasgow team. The results will be presented at the SofTMech Workshop in the LHMC workshop (March 2019) and in Glasgow (June 2019), and subsequently for journal publications. |
Collaborator Contribution | As above |
Impact | Outcomes not yet reported. |
Start Year | 2018 |
Description | Pump Priming - Optimisation of Nanoband electrochemical Affimer assay |
Organisation | Nanoflex |
Country | United Kingdom |
Sector | Private |
PI Contribution | The project in collaboration with NanoFlex Ltd. built on preliminary work showing that electrochemical impedance measurements of the electroactive species Ferrocenecarboxylic acid on affimer functionalised surfaces, using nanoband array electrodes developed by NanoFlex, had potential application as a highly sensitive diagnostic protein assay. The study used GST (Glutathione S-transferase) as a model protein but represents a generic affimer based approach which would be readily applicable to a wide range of protein markers. |
Collaborator Contribution | As above |
Impact | The electrode was functionalised via the direct adsorption of the affimer to the platinum nano-band electrode, driven by the tags on the affimer. This approach was able to detect changes in the impedance for GST concentrations of 10pM and 130 pM for Pt101D and Pt303D nanoband electrodes in 1 mgmL-1 BSA respectively. This compared with 1180 pM for a 2mm Pt disc electrode. When BSA was excluded from the measurement of GST and using a Pt101D electrode, a 3 pM addition was visible. BSA inclusion did affect the baseline and GST response when compared to its absence, but above 1 mgmL-1 the effect did not change markedly. The results confirmed the expectation that the ultra-low electrode surface area of the nanoband arrays and improved mass transport characteristics means that there is sufficient analyte present in the solution, even at low concentrations, to significantly bind to the affimer present in a matter of minutes, which was clearly not the case for the planar macro electrode. Issues identified were the lack of proof data in more physiological solutions as well as drift in the baseline from the partially exposed electrode surface. Experiments were undertaken to determine the performance of the established system when run in biological matrices (synthetic urine [surine] and human plasma). While the previous work showed that the procedure was able to detect changes in the impedance for GST concentrations of 10pM for Pt101D nanoband electrodes in 10 mgmL-1 BSA, when run in either surine or human plasma, there was little to no detection of GST. To counter this and to reduce baseline drift, the electrode surface was blocked with PEG-thiol under a variety of conditions. The results confirm the expectation that PEG does improve the surface stability and also significantly reduced both the amount of BSA binding to the affimer modified electrodes as well as the stabilisation time. However, it did also dampen the electrode response to GST which suggests that PEG is either removing some affimer when it binds to the surface or inhibits its function in some way. Affinity fits to the data give KD values in the low to sub nM range, which is in the expected range for the affimer. It is possible that the previously unblocked surface provides an avidity type effect which could account for the particularly low detection levels seen with the unblocked surface. Testing the functionalised surfaces in surine and human plasma against GST failed to show a significant response. The project has clearly shown that nanoband array electrode structures do provide significant advantages over planar macro electrodes with respect to binding very low concentration analytes from solution. However, there is clearly still significant work to be done on the electrode surface treatment and affimer immobilisation protocols. |
Start Year | 2017 |
Description | Pump Priming - Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data |
Organisation | City, University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am applying for pump priming funding to cover expenses towards preparation fora grant proposal on "Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data" to be submitted to the MRC on 14 November (MRC Methodology Research Panel). My overarching ambition is to develop a new field of data analytics - spatio-temporal statistical learning methods for imaging and functional data - to deliver a revolutionary improvement in statistical methodology and to apply them for more precise utilisation of routinely collected imaging data toward more precise, cost-effective and point-of-care management of eye diseases. Past work (the proof of concept): In the last twelve months I have lead and developed a proof-of-concept spatial statistical methodology and software development for analysis of retinal images. We did two works. First, we developed spatial model that evaluates the association between the capillary non-perfusion and survival of children with malarial retinopathy (MacCormick et al., Sci Rep 2017). Second, we developed a spatial model of shape of optic nerve head and derived a diagnostic tool for detection of glaucoma in eyes (manuscript in preparation for submission) which is an extension of our work on epilepsy (Hughes et al. SMMR 2016, Stat in Medicine 2017). Our work on capillary non-perfusion helps to understand that capillary non-perfusion is important risk factor for death outcome. Our glaucoma detection tool gives accuracy of 97% which is a dramatic increase from 84% accuracy of machine learning approaches. For example, in the future the optometrists can have an application that will tell them the probability of glaucoma and will recommend the patient to be send to a clinic. The projected number of people affected with glaucoma worldwide is estimated to reach 111.8 million in 2040; with the majority of patients in Asia and Africa. Our method will lead to better screening and to improved diagnosis of glaucoma and consequently to improved health outcome. This proof-of-concept has been an effort of a team lead by Dr Gabriela Czanner. It has involved ? Imaging specialists: Dr Bryan Williams (U of Liverpool), Dr Silvester Czanner (Manchester Metropolitan University), ? Clinicians: Rob Cheeseman and Dr Ian MacCormick, Prof Simon Harding (U of Liverpool and Royal Liverpool University Hospital), and Prof Colin Willoughby (Belfast), ? Machine learning: Dr Kun Li (Taishan Medical College, China) and Dr Yalin Zheng (U of Liverpool), ? Statisticians: Dr Gabriela Czanner (U of Liverpool), Prof Emery Brown (Harvard/MIT) and Prof Peter Diggle (CHICAS, Lancaster). The proposed activity and its novelty: I am proposing to - Prepare grant proposal and apply for grants: MRC MRP (14 November 2018) - Organise two scoping meetings in Liverpool. The aim of the scoping meetings will be to work on grant proposal, the external visitors will be asked to give a seminar. Other meetings will be facilitated via skype and email. - One visit to City University (Prof David Crabb) and one visits to Lancaster CHICAS (UK). - One visit to Prof Emery Brown and Eye and Ear Infirmary hospital (Boston, USA). Skype meetings will be scheduled with Prof Brown to discuss the details for the grant proposal. One visit of Dr Czanner will be planned to Boston, to meet his team and to set up a collaboration and data sharing with the Eye and Ear Infirmary hospital in Boston. |
Collaborator Contribution | As above |
Impact | Not reported yet. |
Start Year | 2018 |
Description | Pump Priming - Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data |
Organisation | Lancaster University |
Department | Centre for Health Informatics, Computing, and Statistics (CHICAS) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am applying for pump priming funding to cover expenses towards preparation fora grant proposal on "Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data" to be submitted to the MRC on 14 November (MRC Methodology Research Panel). My overarching ambition is to develop a new field of data analytics - spatio-temporal statistical learning methods for imaging and functional data - to deliver a revolutionary improvement in statistical methodology and to apply them for more precise utilisation of routinely collected imaging data toward more precise, cost-effective and point-of-care management of eye diseases. Past work (the proof of concept): In the last twelve months I have lead and developed a proof-of-concept spatial statistical methodology and software development for analysis of retinal images. We did two works. First, we developed spatial model that evaluates the association between the capillary non-perfusion and survival of children with malarial retinopathy (MacCormick et al., Sci Rep 2017). Second, we developed a spatial model of shape of optic nerve head and derived a diagnostic tool for detection of glaucoma in eyes (manuscript in preparation for submission) which is an extension of our work on epilepsy (Hughes et al. SMMR 2016, Stat in Medicine 2017). Our work on capillary non-perfusion helps to understand that capillary non-perfusion is important risk factor for death outcome. Our glaucoma detection tool gives accuracy of 97% which is a dramatic increase from 84% accuracy of machine learning approaches. For example, in the future the optometrists can have an application that will tell them the probability of glaucoma and will recommend the patient to be send to a clinic. The projected number of people affected with glaucoma worldwide is estimated to reach 111.8 million in 2040; with the majority of patients in Asia and Africa. Our method will lead to better screening and to improved diagnosis of glaucoma and consequently to improved health outcome. This proof-of-concept has been an effort of a team lead by Dr Gabriela Czanner. It has involved ? Imaging specialists: Dr Bryan Williams (U of Liverpool), Dr Silvester Czanner (Manchester Metropolitan University), ? Clinicians: Rob Cheeseman and Dr Ian MacCormick, Prof Simon Harding (U of Liverpool and Royal Liverpool University Hospital), and Prof Colin Willoughby (Belfast), ? Machine learning: Dr Kun Li (Taishan Medical College, China) and Dr Yalin Zheng (U of Liverpool), ? Statisticians: Dr Gabriela Czanner (U of Liverpool), Prof Emery Brown (Harvard/MIT) and Prof Peter Diggle (CHICAS, Lancaster). The proposed activity and its novelty: I am proposing to - Prepare grant proposal and apply for grants: MRC MRP (14 November 2018) - Organise two scoping meetings in Liverpool. The aim of the scoping meetings will be to work on grant proposal, the external visitors will be asked to give a seminar. Other meetings will be facilitated via skype and email. - One visit to City University (Prof David Crabb) and one visits to Lancaster CHICAS (UK). - One visit to Prof Emery Brown and Eye and Ear Infirmary hospital (Boston, USA). Skype meetings will be scheduled with Prof Brown to discuss the details for the grant proposal. One visit of Dr Czanner will be planned to Boston, to meet his team and to set up a collaboration and data sharing with the Eye and Ear Infirmary hospital in Boston. |
Collaborator Contribution | As above |
Impact | Not reported yet. |
Start Year | 2018 |
Description | Pump Priming - Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data |
Organisation | Massachusetts Eye and Ear Infirmary |
Country | United States |
Sector | Hospitals |
PI Contribution | I am applying for pump priming funding to cover expenses towards preparation fora grant proposal on "Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data" to be submitted to the MRC on 14 November (MRC Methodology Research Panel). My overarching ambition is to develop a new field of data analytics - spatio-temporal statistical learning methods for imaging and functional data - to deliver a revolutionary improvement in statistical methodology and to apply them for more precise utilisation of routinely collected imaging data toward more precise, cost-effective and point-of-care management of eye diseases. Past work (the proof of concept): In the last twelve months I have lead and developed a proof-of-concept spatial statistical methodology and software development for analysis of retinal images. We did two works. First, we developed spatial model that evaluates the association between the capillary non-perfusion and survival of children with malarial retinopathy (MacCormick et al., Sci Rep 2017). Second, we developed a spatial model of shape of optic nerve head and derived a diagnostic tool for detection of glaucoma in eyes (manuscript in preparation for submission) which is an extension of our work on epilepsy (Hughes et al. SMMR 2016, Stat in Medicine 2017). Our work on capillary non-perfusion helps to understand that capillary non-perfusion is important risk factor for death outcome. Our glaucoma detection tool gives accuracy of 97% which is a dramatic increase from 84% accuracy of machine learning approaches. For example, in the future the optometrists can have an application that will tell them the probability of glaucoma and will recommend the patient to be send to a clinic. The projected number of people affected with glaucoma worldwide is estimated to reach 111.8 million in 2040; with the majority of patients in Asia and Africa. Our method will lead to better screening and to improved diagnosis of glaucoma and consequently to improved health outcome. This proof-of-concept has been an effort of a team lead by Dr Gabriela Czanner. It has involved ? Imaging specialists: Dr Bryan Williams (U of Liverpool), Dr Silvester Czanner (Manchester Metropolitan University), ? Clinicians: Rob Cheeseman and Dr Ian MacCormick, Prof Simon Harding (U of Liverpool and Royal Liverpool University Hospital), and Prof Colin Willoughby (Belfast), ? Machine learning: Dr Kun Li (Taishan Medical College, China) and Dr Yalin Zheng (U of Liverpool), ? Statisticians: Dr Gabriela Czanner (U of Liverpool), Prof Emery Brown (Harvard/MIT) and Prof Peter Diggle (CHICAS, Lancaster). The proposed activity and its novelty: I am proposing to - Prepare grant proposal and apply for grants: MRC MRP (14 November 2018) - Organise two scoping meetings in Liverpool. The aim of the scoping meetings will be to work on grant proposal, the external visitors will be asked to give a seminar. Other meetings will be facilitated via skype and email. - One visit to City University (Prof David Crabb) and one visits to Lancaster CHICAS (UK). - One visit to Prof Emery Brown and Eye and Ear Infirmary hospital (Boston, USA). Skype meetings will be scheduled with Prof Brown to discuss the details for the grant proposal. One visit of Dr Czanner will be planned to Boston, to meet his team and to set up a collaboration and data sharing with the Eye and Ear Infirmary hospital in Boston. |
Collaborator Contribution | As above |
Impact | Not reported yet. |
Start Year | 2018 |
Description | Pump Priming - Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data |
Organisation | University of Liverpool |
Department | Institute of Translational Medicine |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | I am applying for pump priming funding to cover expenses towards preparation fora grant proposal on "Transforming spatio-temporal statistical learning methods: for complex clinical datasets that contain imaging data" to be submitted to the MRC on 14 November (MRC Methodology Research Panel). My overarching ambition is to develop a new field of data analytics - spatio-temporal statistical learning methods for imaging and functional data - to deliver a revolutionary improvement in statistical methodology and to apply them for more precise utilisation of routinely collected imaging data toward more precise, cost-effective and point-of-care management of eye diseases. Past work (the proof of concept): In the last twelve months I have lead and developed a proof-of-concept spatial statistical methodology and software development for analysis of retinal images. We did two works. First, we developed spatial model that evaluates the association between the capillary non-perfusion and survival of children with malarial retinopathy (MacCormick et al., Sci Rep 2017). Second, we developed a spatial model of shape of optic nerve head and derived a diagnostic tool for detection of glaucoma in eyes (manuscript in preparation for submission) which is an extension of our work on epilepsy (Hughes et al. SMMR 2016, Stat in Medicine 2017). Our work on capillary non-perfusion helps to understand that capillary non-perfusion is important risk factor for death outcome. Our glaucoma detection tool gives accuracy of 97% which is a dramatic increase from 84% accuracy of machine learning approaches. For example, in the future the optometrists can have an application that will tell them the probability of glaucoma and will recommend the patient to be send to a clinic. The projected number of people affected with glaucoma worldwide is estimated to reach 111.8 million in 2040; with the majority of patients in Asia and Africa. Our method will lead to better screening and to improved diagnosis of glaucoma and consequently to improved health outcome. This proof-of-concept has been an effort of a team lead by Dr Gabriela Czanner. It has involved ? Imaging specialists: Dr Bryan Williams (U of Liverpool), Dr Silvester Czanner (Manchester Metropolitan University), ? Clinicians: Rob Cheeseman and Dr Ian MacCormick, Prof Simon Harding (U of Liverpool and Royal Liverpool University Hospital), and Prof Colin Willoughby (Belfast), ? Machine learning: Dr Kun Li (Taishan Medical College, China) and Dr Yalin Zheng (U of Liverpool), ? Statisticians: Dr Gabriela Czanner (U of Liverpool), Prof Emery Brown (Harvard/MIT) and Prof Peter Diggle (CHICAS, Lancaster). The proposed activity and its novelty: I am proposing to - Prepare grant proposal and apply for grants: MRC MRP (14 November 2018) - Organise two scoping meetings in Liverpool. The aim of the scoping meetings will be to work on grant proposal, the external visitors will be asked to give a seminar. Other meetings will be facilitated via skype and email. - One visit to City University (Prof David Crabb) and one visits to Lancaster CHICAS (UK). - One visit to Prof Emery Brown and Eye and Ear Infirmary hospital (Boston, USA). Skype meetings will be scheduled with Prof Brown to discuss the details for the grant proposal. One visit of Dr Czanner will be planned to Boston, to meet his team and to set up a collaboration and data sharing with the Eye and Ear Infirmary hospital in Boston. |
Collaborator Contribution | As above |
Impact | Not reported yet. |
Start Year | 2018 |
Description | Quantification of uncertainty within systems pharmacology to optimise personalised therapy |
Organisation | University of Liverpool |
Department | Institute for Risk and Uncertainty |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Designed a research proposal and training plan for MRC Skills Development Fellowship. |
Collaborator Contribution | Provision of expertise and academic guidance as fellowship sponsor (Prof Scott Ferson). |
Impact | Outcome of this collaboration was Dr Joseph Leedale (Theme 1) successfully awarded the MRC Skills Development Fellowship. |
Start Year | 2018 |
Description | Theme 1 (Multi-scale Modeling) Project 1 |
Organisation | Royal Liverpool University Hospital |
Department | Department of Vascular Service |
Country | United Kingdom |
Sector | Hospitals |
PI Contribution | We provided the vital mathematical modeling and analysis of the stenting problem |
Collaborator Contribution | Designed and Participated in the project. Helped establishing industrial links to the Centre. |
Impact | - 1 research paper - 1 joint workshop - 1 EPSRC industrial iCase studentship award |
Start Year | 2015 |
Description | Theme 1 Asymptotic ``hydraulics-type'' approximations for pressure redistribution within the abnormal brain vascular network subject to stenting |
Organisation | The Walton Centre |
Country | United Kingdom |
Sector | Hospitals |
PI Contribution | Prof Alexander Movchan and Dr Arun Chandaran ( Walton Centre) has investigates teh new idea of applying athematical modelling to the new stenting process linked to the blood flow within the brain network. They can explain how excessive pressure in the brain is produced and why it affects the vascular network and, in particular, the blood supply to the eye nerves. |
Collaborator Contribution | Real patients data were considered and a good match with modeling is observed. Thsi is very prelinminary and yet promising work. |
Impact | Furher grants applications are planned. |
Start Year | 2020 |
Description | Theme 2 (Imaging and Data Integration) Project 1 |
Organisation | Mirada Medical Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | We are providing the analysis model, mathematical techniques and software for image analysis |
Collaborator Contribution | Helped the design of this industrial project whcih has mathematical challenge to tackle |
Impact | - Draft papers being finalized - Test software almost ready for industrial validation |
Start Year | 2015 |
Description | Theme 2: Dr. Kenneth Mangion (BHF Glasgow Cardiovascular Research Centre) and Dr. Hao Gao (University of Glasgow) |
Organisation | British Heart Foundation (BHF) |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Theme 2: Dr Anis Theljani & Professor Ke Chen have ongoing work in collaboration with Dr. Kenneth Mangion (BHF Glasgow Cardiovascular Research Centre) and Dr. Hao Gao (University of Glasgow). We aim to apply registration techniques for strain estimation in cardiology. We have applied for pump-priming proposal "Development of AI-Segmentation and Registration for Heart Imaging '' from both the Liverpool centre and SofTMech. Our methods have been tested with BHF Glasgow Cardiovascular Research Centre's data and the initial results are promising. |
Collaborator Contribution | The partners have supplied us with data so we can test our methods. |
Impact | Initial results are promising - no impact recorded yet. |
Start Year | 2018 |
Description | Theme 2: Dr. Kenneth Mangion (BHF Glasgow Cardiovascular Research Centre) and Dr. Hao Gao (University of Glasgow) |
Organisation | University of Glasgow |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Theme 2: Dr Anis Theljani & Professor Ke Chen have ongoing work in collaboration with Dr. Kenneth Mangion (BHF Glasgow Cardiovascular Research Centre) and Dr. Hao Gao (University of Glasgow). We aim to apply registration techniques for strain estimation in cardiology. We have applied for pump-priming proposal "Development of AI-Segmentation and Registration for Heart Imaging '' from both the Liverpool centre and SofTMech. Our methods have been tested with BHF Glasgow Cardiovascular Research Centre's data and the initial results are promising. |
Collaborator Contribution | The partners have supplied us with data so we can test our methods. |
Impact | Initial results are promising - no impact recorded yet. |
Start Year | 2018 |
Description | Theme 2: Royal Liverpool and Broadgreen University Hospitals NHS Trust |
Organisation | Royal Liverpool and Broadgreen University Hospitals NHS Trust |
Country | United Kingdom |
Sector | Public |
PI Contribution | Theme 2: Working as partners with Royal Hospital we developed a novel data efficient and accurate glaucoma detection algorithm based on optic disc deformation (MacCormick et al., accepted for a publication in PLOSONE). We used the Royal Hospital's data to find our initial results and we are now approaching several hospitals in the UK for further clinical data to further validate the algorithm and to extend it into longitudinal data. |
Collaborator Contribution | Expertise on glaucoma detection based on optic disc deformation and data for testing our methods. |
Impact | The following journal was published following work in this partnership: MacCormick IJC, Williams BM, Zheng Y, Li K, Al-Bander B, Czanner S, Cheeseman R, Willoughby CE, Brown ENB, Spaeth GL, Czanner G. Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile. PLOSONE. Accepted 6 Dec 2018. |
Start Year | 2018 |
Description | Theme 3 Collaboration with World Health Organization |
Organisation | World Health Organization (WHO) |
Country | Global |
Sector | Public |
PI Contribution | Modelling seasonal influenza incidence and evolutionary dynamics. . Participation in bi-weekly teleconference calls. This (hopefully) will also lead to engagement when we relay our findings back to WHO. |
Collaborator Contribution | WHO are providing up-to-date data gathered from their surveillance system. Participation in bi-weekly teleconference calls. |
Impact | Ongoing work |
Start Year | 2016 |
Description | Theme 3 Collaboration with World Health Organization |
Organisation | World Health Organization (WHO) |
Country | Global |
Sector | Public |
PI Contribution | Modelling seasonal influenza incidence and evolutionary dynamics. . Participation in bi-weekly teleconference calls. This (hopefully) will also lead to engagement when we relay our findings back to WHO. |
Collaborator Contribution | WHO are providing up-to-date data gathered from their surveillance system. Participation in bi-weekly teleconference calls. |
Impact | Ongoing work |
Start Year | 2016 |
Description | Wenzhou |
Organisation | Wenzhou Medical University |
Country | China |
Sector | Academic/University |
PI Contribution | Topography analysis based on techniques developed in EPSRC project |
Collaborator Contribution | Collection and analysis of a huge set of topography maps |
Impact | A number of papers linked to this projects have been produced as a result of this collaboration. |
Start Year | 2015 |
Description | 7 Talks by the Liverpool Group / LCMH at SIAM Conference on Imaging Science, June 5-8, 2018, Bologna - Italy. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | 7 Talks by the Liverpool Group / LCMH at SIAM Conference on Imaging Science, June 5-8, 2018, Bologna - Italy. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.siam-is18.dm.unibo.it/ |
Description | Bi-Weekly PDRA Seminars |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Bi-weekly meetings between all PDRA's and Post Graduate students at the EPSRC Liverpool Centre for Mathematics in Healthcare where presentations and updates are given and feedback is received. |
Year(s) Of Engagement Activity | 2017,2018,2019 |
Description | British Applied Mathematics Colloquium. BAMC 2017, University of Surrey, UK (April 10-12, 2017) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | The talk delivered is S. Frecentese, G. Carta, L.P. Argani, A.B. Movchan, N.V. Movchan, M.L. Wall, "Bloch waves in blood vessels with stents" |
Year(s) Of Engagement Activity | 2017 |
Description | British Science Festival - Public engagement and outreach |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | The Centre is keen to explain what we do to the public. In 2007, we took part in this Public engagement and outreach. A. Movchan and L. Argani have presented an event at the British Science Festival, Mathematical Events 2017. Brighton, 5-9 September 2017 (Friday 8 September, 16.30-17.30, A2, Asa Briggs Arts, University of Sussex), entitled ``Towards better aneurysm treatments'', which attracted a lot of interest from experts and members of the general public. |
Year(s) Of Engagement Activity | 2017 |
URL | https://www.britishscienceassociation.org/british-science-festival |
Description | Centre workshop 1 - Sept 2016 |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Imaging workshop where we reported our projects and findings, invited industrial partners to tell us their challenges in their work. The networking event is well received. |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.tinyurl.com/EPSRC-LCMH |
Description | Centre workshop 2 |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Stenting for abdominal aortic aneurysms - modeling experts met clinicians and industrial partners and new / potential collaborators. New results are highlighted and new problems are identified. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.tinyurl.com/EPSRC-LCMH |
Description | Co-supervision of PhD student |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Co-supervision of PhD student Hawre Salih by Prof Ke Chen, Dr Tuomo Valkonen and Dr Anna Pratoussevitch. |
Year(s) Of Engagement Activity | 2017,2018 |
Description | Dr Joseph Leedale - Multiscale modelling of drug transport in systems pharmacology Seminar at the QSP UK Exchange Workshop, Reading |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Dr Joseph Leedale gave a talk entitled 'Multiscale modelling of drug transport in systems pharmacology' at the Quantitative Systems Pharmacology (QSP) UK Exchange Workshop, University of Reading (July 2018). |
Year(s) Of Engagement Activity | 2018 |
Description | Dr Joseph Leedale displayed his poster 'Multiscale modelling of drug transport in systems pharmacology' at STEM for BRITAIN 2018, House of Commons. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | Dr Joseph Leedale displayed his poster 'Multiscale modelling of drug transport in systems pharmacology' at STEM for BRITAIN 2018, House of Commons, Westminster, London (March 2018). |
Year(s) Of Engagement Activity | 2018 |
Description | Dynamic Response of Stents in Vascular Systems |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation at The European Society for Vascular Surgery 33rd Annual Meeting, 24-27 September 2019, Hamburg, Germany The presentation was given to medical professionals on the recent advance in the analysis of the dynamic response of structrured stents and partially obstructed blood vessels. |
Year(s) Of Engagement Activity | 2019 |
Description | European Symposium on Vascular Biomaterials - ESVB 2017, Strasbourg, France (October 12-14, 2017) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | L.P. Argani, F. Torella, R.K. Fisher, R.G. McWilliams, M.L. Wall, A.B. Movchan, "Modelling of deformation and dynamic response of abdominal aortic aneurysms treated by endovascular sealing" - L.P. Argani was selected among the 8 finalist for the Young Researcher Prize |
Year(s) Of Engagement Activity | 2017 |
Description | FLUENCE workshop in Nijmegen |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was a workshop to intrude a group of UK scientists to the use of the FELIX free electron lasers in Nijmegen |
Year(s) Of Engagement Activity | 2018 |
Description | Five Centres Mathematics for Healthcare Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | FIVE EPSRC Maths-Healthcare Centres (Cambridge, Exeter, Imperial, Liverpool and SofTMech) gathered together from the 19th to the 21st September 2018 at the University of Glasgow to exchange success stories and share experiences, and more importantly to consider future funding. Kings College London, UCLouvain, the University of Lancaster, Terumo Aortic and The Sick Children's Hospital in Glasgow were also represented by speakers who had been invited by one of the centres. Each of the Centres had recently completed their Mid-Term Review. Two portfolio Managers from the EPSRC, who fund the five centres attended, giving the centres the perspective of the EPSRC, as they discussed the way forward. This was the first of two workshops. The centres gave an overview of the work at their centre, in particular highlighting new and exciting work where collaboration with other UK expertise would form a stronger funding application. In addition to the external speakers each centre had a number of internal speakers who gave presentations on their research and how it fitted in with the overall theme of their Maths and Healthcare Centre. |
Year(s) Of Engagement Activity | 2018 |
URL | http://www.softmech.org/events/headline_593316_en.html |
Description | HFML-FELIX User Meeting 2019, FELIX, Nijmegen, The Netherlands, (8-9 July 2019) Invited talk by Michele Siggel-King |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was a working group to design a scientific instrument. |
Year(s) Of Engagement Activity | 2019 |
Description | IMA/QJMAM Summer School on Asymptotics of PDEs and Modelling of Waves |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was International Summer School aimed at a wide range audience interested in partial differential equations, their applications and in particular lectures were delivered on Mathematical modelling of metamaterials structures and vascular systems networks and their dynamic response. |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.eventbrite.co.uk/e/qjmamima-summer-school-on-asymptotics-of-pdes-and-modelling-of-waves-... |
Description | Infectious Disease Modelling Summer School |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Two week-long workshop held in Japan for public health practitioners and graduate students to develop a practical understanding of infectious disease modelling. Read was delivered sessions on seasonal influenza epidemiology and modelling epidemics in structured populations. Audience was drawn from Japan as well as other countries in the region (including South Korea, China, Indonesia, Philippines). |
Year(s) Of Engagement Activity | 2016 |
URL | https://sites.google.com/site/modelinfection/home/shortcourse3 |
Description | Interdisciplinary EPSRC Workshop "Elastic deformation and dynamic response of aneurysm repairs: modelling and applications" (Liverpool, UK, February 2017) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This interdisciplinary workshop attracted leading scientists, applied mathematicians and medical practitioners from the UK, USA, Netherlands, Italy. The workshop has focused on the practical and theoretical aspects of abdominal aortic aneurysms, and in particular EVAS treatment. The Liverpool group and their partners have contributed six presentations to this event: S. Frecentese, "Modelling of waves in stented blood vessels" L.P. Argani, "Modelling of deformation and dynamic response of abdominal aneurysm sealing" F. Torella, "Introduction to AAA, EVAR and EVAS" R.K. Fisher, "Modes and mechanisms of failure of EVAR/EVAS" R.G. McWilliams, "Methods of imaging surveillance after EVAS/EVAR" M.L. Wall, "Aneurysm rupture - theoretical and practical challenges" |
Year(s) Of Engagement Activity | 2017 |
Description | Invited Seminar, EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Invited seminar at the EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter. Useful discussions during and afterwards which have highlighted important new techniques that could help optimise my current approach. |
Year(s) Of Engagement Activity | 2017 |
Description | Invited Talk at "Efficient Operator Splitting Techniques for Complex System and Large Scale Data Analysis 2019", Sanya International Forum, Jan 14-18 2019. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Invited Talk at "Efficient Operator Splitting Techniques for Complex System and Large Scale Data Analysis 2019", Sanya International Forum, Jan 14-18 2019. |
Year(s) Of Engagement Activity | 2019 |
Description | Invited Talk at "ICCM Consortium conference on Computational and Applied Mathematics", Nanjing, Dec 10-14, 2018. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Professor Ke Chen - Theme 2: Invited Talk at "ICCM Consortium conference on Computational and Applied Mathematics", Nanjing, Dec 10-14, 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | Invited Talk at "International Conference on Scientific Computing", CUHK, Hong Kong, 5-8 December, 2018. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Professor Ke Chen. Invited Talk at "International Conference on Scientific Computing", CUHK, Hong Kong, 5-8 December, 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | Invited Talk at "International Workshop On Image Processing and Inverse Problems", Beijing, April 21-24, 2018 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Invited Talk at "International Workshop On Image Processing and Inverse Problems", Beijing, April 21-24, 2018 |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.csrc.ac.cn/en/event/workshop/2017-12-27/78.html |
Description | Invited Talk at Community Meeting: FELIX: Free Electron lasers for the Catalysis Community (18 July 2019) Research Complex at Harwell |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | This was a collaboration meeting of scientists interested in using the FELIX free electron lasers in Nijmegen. |
Year(s) Of Engagement Activity | 2019 |
Description | Invited Talk at the "Workshop on Mathematical Theory and Methods in Image Processing", Hunan Normal University, Changsha, Apr 24-28, 2018. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Professor Ke Chen - Invited Talk at the "Workshop on Mathematical Theory and Methods in Image Processing", Hunan Normal University, Changsha, Apr 24-28, 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | Invited Talk: Japanese Region of International Biometric Society (JR-IBS): Annual seminar 2022 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Japanese Region of International Biometric Society (JR-IBS) has asked me to provide an invited talk in an international session of the annual seminar of JR-IBS in January, 2022. The seminar title of this year was "analysis of correlated data", and requested to present an overview of methods of joint modelling for repeated measures and survival time based on my recent work, including a series of papers published in BMC Medical Research Methodology and other journals. The session was planned as an online conference at 3:00-6:00 p.m., Jan. 22, 2022 in Japanese time, which corresponds to 6:00-9:00 a.m., Jan. 22, 2022 in BST. My presentation was 40 min talk, followed by 10 min of Q&A. This session was jointly hosted by the Institute of Statistical Mathematics. The talk sparked questions and discussion afterwards, and email corresponding after the talk indicted an increased interest in related subject areas. |
Year(s) Of Engagement Activity | 2022 |
Description | Invited lecture on ``Eigenvalue problems in the dynamics of fluid-solid biological systems'' presented at International 5th Soft Tissue Modelling Workshop, 1-3 June 2021 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The invited one hour lecture on ``Eigenvalue problems in the dynamics of fluid-solid biological systems'' was delivered at the international Soft Tissue Modelling Workshop in June 2021 for a large interdisciplinary audience. |
Year(s) Of Engagement Activity | 2021 |
URL | http://www.softmech.org/events/headline_791379_en.html |
Description | Invited presentation at the International Conference for the In Vitro Toxicology Society, London. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited presentation at the International Conference for the In Vitro Toxicology Society, London. Useful discussions afterwards with potential future collaborators. Also, a number of followup meetings planned to develop future collaborations. |
Year(s) Of Engagement Activity | 2017 |
Description | Invited seminar |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | 2nd Feb 2019 "Recent advances in the application of infrared techniques to the study of cancer." Physics Dept. University of Sheffield |
Year(s) Of Engagement Activity | 2019 |
Description | Invited talk - Recent advances in joint models for multivariate longitudinal data and event-times with application to cancer - INSERM, Bordeaux, France. (January 2019) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Theme 2: Invited talk - Recent advances in joint models for multivariate longitudinal data and event-times with application to cancer. Recent advances in joint models for cancer and the new statistical challenge of immunotherapy clinical studies. INSERM, Bordeaux, France. (January 2019) |
Year(s) Of Engagement Activity | 2019 |
Description | Invited talk at TERANEW network meeting, National Physics Laboratory (4 Dec 2019) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was an invited talk at an EPSRC Network TERANET at the National Physical Laboratory. |
Year(s) Of Engagement Activity | 2019 |
Description | Invited talk. Use statistics to build further confidence in your research - University of Liverpool April 2018. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Theme 2: Invited talk. Use statistics to build further confidence in your research. An event which was part of 'How to enhance the impact of your research' series, under Athena SWAN Be Inspired banner to try to promote the involvement of women in research, University of Liverpool April 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | Invited talk. What can statistics do for the understanding of ophthalmic diseases? From measurement errors to inference and discrimination using complex datasets that contain images. (23 and 24 Apr 2018) Royal Society Science (London) (UK) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Theme 2: Invited talk. What can statistics do for the understanding of ophthalmic diseases? From measurement errors to inference and discrimination using complex datasets that contain images. (23 and 24 Apr 2018) Royal Society Science+ meeting. The transformative potential of data and image analysis for eye care. (London) (UK) |
Year(s) Of Engagement Activity | 2018 |
Description | Invited talk: Evaluating the efficacy of longitudinal biomarker for clinical endpoint. International Conference of the European Research Consortium for Informatics and Mathematics Working Group on Computational and methodological Statistics. University of London, (December 2017) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Invited talk: Evaluating the efficacy of longitudinal biomarker for clinical endpoint. International Conference of the European Research Consortium for Informatics and Mathematics Working Group on Computational and methodological Statistics, Special topic: Statistical Evaluation of Medical Diagnostic Tests. University of London, (December 2017) |
Year(s) Of Engagement Activity | 2017 |
Description | Invited talk: Evaluating the time dependent efficacy of a longitudinal biomarker for clinical endpoint. EBio2018, III Portuguese-Galician Meeting of Biometry. Aveiro, Portugal. (June 2018) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Invited talk: Evaluating the time dependent efficacy of a longitudinal biomarker for clinical endpoint. EBio2018, III Portuguese-Galician Meeting of Biometry. Aveiro, Portugal. (June 2018) |
Year(s) Of Engagement Activity | 2018 |
Description | Invited talk: ISPED-Bordeaux School of Public Health & INSERM,University of Bordeaux |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The event is on specific topic to discuss recent advances in joint models for cancer and the new statistical challenge of immunotherapy clinical studies. The audience was interdisciplinary, and sparked many questions and discussions afterwards, and later through e-mail showing an increased interest in the topic I presented. |
Year(s) Of Engagement Activity | 2019 |
URL | http://www.canceropole-gso.org/page/manifestations/journees-du-club-smac/642-recent-advances-in-join... |
Description | Invited talk: Joint modelling of longitudinal data and event-times with applications in health research. Joint RSS Highland Group Annual meeting, University of St Andrews. June 05, 2019. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | The talk sparked many questions and discussions afterwards, showing an increased interest in the topic. |
Year(s) Of Engagement Activity | 2019 |
URL | http://www.bioss.ac.uk/RSSH/previoushighland.html |
Description | Invited visit to present work at Unilever |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | Invited visit to present work at Unilever. Useful discussions that has helped align my work with more relevant industrial impact. Discussions ongoing regarding development of future collaborations and shared grant applications. |
Year(s) Of Engagement Activity | 2017 |
Description | Liverpool - Glasgow Healthcare Modelling Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Date: Thursday 30th August 2018 Time: 12:00 -17:30 Venue: Stephenson Institute for Renewable Energy (SIRE) Seminar Room, Chadwick Building This is the 2nd Joint meeting of two EPSRC Maths Healthcare Modelling Centres (Glasgow University and The University of Liverpool). It will showcase works from both centres with presentations and posters from Academics, PDRA's and PHD's from both Universities highlighting new results and emerging healthcare challenges. The main purpose of the networking workshop is to promote and facilitate new research collaborations between the TWO Universities. Pump-priming projects jointly funded by both Centres will be discussed and formed, growing out of the event as preperation for subsequent national and international grant applications. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.liverpool.ac.uk/mathematical-sciences/research/centre-for-mathematics-in-healthcare/30-a... |
Description | Liverpool Cell Imaging annual workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | The Centre for Cell Imaging organised a 2 day workshop focused on light microscopy techniques, imaging probes and image analysis. 90 researchers and students attended the event mainly from Liverpool and Manchester but also from other Universities in the UK. Industrial partners were invited and attended.The second day was a focused hands-on training on image analysis. |
Year(s) Of Engagement Activity | 2018 |
URL | https://cci.liv.ac.uk/2018_workshop.html |
Description | Liverpool John Moores Univeristy - Invited Seminar - Dr Joseph Leedale |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Dr Joseph Leedale gave a seminar entitled 'Multiscale modelling of drug transport in systems pharmacology' at Liverpool John Moores Univesity. October 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | Maths club |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Presented research on maths for health to 6th form students who attend University maths club. |
Year(s) Of Engagement Activity | 2020 |
URL | http://www.maths.liv.ac.uk/~mathsclub/index.php |
Description | National Conference on the application of terahertz radiation to the study of cancer |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | An invited talk on "Characteristics of cancerous tissue in the THz region of the electromagnetic spectrum." |
Year(s) Of Engagement Activity | 2018 |
Description | One day industrial research meeting in London with representatives of Vascutek/Terumo Aortic |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Industry/Business |
Results and Impact | The one day industrial meeting with representatives of Vascutek/Terumo Aortic has taken place in London on the 25th April 2018. The research group included Prof A. Movchan, Prof N. Movchan, Dr L. Argani, Miss S. Frecentese, Mr. M. Wall, Two research presentations have been given, and technical discussion was carried out with Dr T. Pacuka and his colleagues from R&D of Terumo Aortic. The meeting was highly productive and has delivered several research outcomes outlining directions for collaboration and for a joint research proposal. |
Year(s) Of Engagement Activity | 2018 |
Description | Organisation of a workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | A 2 days workshop on imaging and image analysis, attended by scientists and postgraduate students from University of Liverpool and beyond as well as by company representatives (100 attendees). |
Year(s) Of Engagement Activity | 2020 |
URL | https://cci.liv.ac.uk/2019_2020_workshop.html |
Description | Outreach activity |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | Local school children attended a science fair prior to the screening of the Royal Institution Christmas Lecture. The theme of our exhibit was mathematics and imaging |
Year(s) Of Engagement Activity | 2019 |
Description | Outreach activity at the Liverpool World Museum |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | The Centre for Cell Imaging led an exhibition at the World Museum in Liverpool, as part of the "Meet the Scientist" scheme. The exhibit was entitled "seeing is believing". Members of the public, including children engaged in a numerous of activities around microscopy and bio-imaging. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.liverpool.ac.uk/health-and-life-sciences/public-engagement/events/meet-the-scientists/ |
Description | Participantion in the Assessment Panel of Engineering and Physica Sciences Research Council |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | I was invited to oarticipane in the expert EPSRC panel in Modelling in Healthcare in February 2021 |
Year(s) Of Engagement Activity | 2022 |
Description | Poster - Multiscale modelling of drug transport in systems pharmacology' Won award at INCOME 2018 Conference and Hackathon |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Dr Joseph Leedale presented his poster entitled 'Multiscale modelling of drug transport in systems pharmacology' at the Integrative Pathway Modelling in Systems Biology and Systems Medicine (INCOME) 2018 Conference and Hackathon, Bernried, Lake Starnberg, Germany. (October 2018). Jospph won first prize which was 400 euros. |
Year(s) Of Engagement Activity | 2018 |
Description | Poster presentation at UK Quantitative Systems Pharmacology Network Exchange Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Interest in using model by colleagues in pharma industry |
Year(s) Of Engagement Activity | 2019 |
Description | Presentation on Emergence risks associated with A(H7N9) Avian Influenza in China. Venue: USA State Department |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | A(H7N9) Avian Influenza in China workshop |
Year(s) Of Engagement Activity | 2017 |
Description | Presented at Developments in Healthcare Imaging - Connecting with Academia, University of Cambridge, (May 2018) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Presented at Developments in Healthcare Imaging - Connecting with Academia, University of Cambridge, (May 2018) |
Year(s) Of Engagement Activity | 2018 |
URL | https://gateway.newton.ac.uk/event/tgmw58/programme |
Description | Presented at Leverhulme Research Centre Harnessing Exponential Growth workshop, University of Liverpool (September 2017) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Postgraduate students |
Results and Impact | Theme 2: Presented at Leverhulme Research Centre Harnessing Exponential Growth workshop, University of Liverpool (September 2017) |
Year(s) Of Engagement Activity | 2017 |
Description | Presented at One day joint workshop LCMH-GSK London, (July 2018) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Theme 2: Presented at One day joint workshop LCMH-GSK London, (July 2018) |
Year(s) Of Engagement Activity | 2018 |
Description | Prof R Bearon invited speaker at workshop on 'Mathematical Challenges in the Analysis of Continuum Models for Cancer Growth, Evolution and Therapy'. CMO, Oaxaxo, Mexico |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Professor Rachel Bearon was an invited speaker at workshop on 'Mathematical Challenges in the Analysis of Continuum Models for Cancer Growth, Evolution and Therapy'. CMO, Oaxaxo, Mexico. (November 2018). |
Year(s) Of Engagement Activity | 2018 |
Description | Research Discussion events with the vascular surgery group at the Royal Liverpool Hospital |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | The puprose of the research discussion events was to discuss the outcomes of the mathematical model in the context patient specific geometries and shapes of aneurysms. The meetings were very productive and technically stimulating. |
Year(s) Of Engagement Activity | 2017,2018,2019 |
Description | Research Visit to the Walton Centre for Brain Surgery |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | The LCMH research group, Prof K.Chen, Prof A. Movchan and Ms S. Frecentese have visited the vascular department of the Walton Centre with the presentation of the mathematical modelling work to explore the avenue for the long term collaboration. Vascular surgeons of the Walton Centre are particularly interested in modelling of a complex procedure related to installation of metal stents into the selected sections of the brain vascular systems. This concerns with certain group of patients whose internal pressure of brain tissues is above the admissible level and hence some blood vessels collapse, which leads to the disruption of the blood supply of vital organs. |
Year(s) Of Engagement Activity | 2018,2019 |
Description | Research discussion with vascular surgeons on prospective joint research on modelling of brain vascular networks, 16 December 2020, Walton Centre Liverpool |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | The LCMH research group, Prof K.Chen, Prof A. Movchan have proposed a new model to the vascular department of the Walton Centre with the the avenue for a joint grant proposal. Vascular surgeons of the Walton Centre in Liverpool are performing a complex procedure related to installation of metal stents into the selected sections of the brain vascular systems. Analysis of the redistribution of pressure within the network is essential, and the new model delivers this outcome in the transient regime. |
Year(s) Of Engagement Activity | 2019 |
Description | Scientific oral presentation at the Dynamic Cell conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Oral presentation of Research data on 3D imaging of cell invasion. |
Year(s) Of Engagement Activity | 2018 |
URL | https://bscb.org/meeting/dynamic-cell-iii/ |
Description | THz Imaging of Cancer, London (12 July 2019) Invited Talk (PW) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | This was an invited talk at a conference on application of Terahertz radiation in health care |
Year(s) Of Engagement Activity | 2019 |
Description | The Fundamentals of Late Stage Cancer Meeting, NorthWest Cancer Research Centre, University of Liverpool (19-20 Sept 2019) Poster Presentation |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was a conference on problems in the treatment of late stage cancer. |
Year(s) Of Engagement Activity | 2019 |
Description | The Vascular Societies' Annual Scientific Meeting 2017, Manchester Central, UK (November 22-24, 2017) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The talk delivered at the meeting was S. Frecentese, G. Carta, L.P Argani, A.B. Movchan, N.V. Movchan, M.L. Wall, "Wave propagation and fluid-structure interaction in stented blood vessels" |
Year(s) Of Engagement Activity | 2017 |
Description | Theme 1: Faculty of Science and Engineering Poster Day 2018 |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | The annual event gives full-time second year and part-time third and fourth year postgraduate research students (PGRs) the opportunity to showcase their work to a wider academic audience and gain feedback from peers and research professionals. Commenting on the event, FSE Director for PGR Professor David Joss, said: "Faculty Poster Days serve as a social and interdisciplinary networking event where learning, feedback and information are freely exchanged in a friendly and supportive environment. It is the perfect opportunity for like-minded people to get together and learn more about the research currently being undertaken at the University." Five prizes were awarded at the event including prizes for each of the schools in the Faculty of Science and Engineering and an overall winner for the day. Sara Frecentese from the School of Physical Sciences (LCMH) won for her poster on 'Waves and fluid-solid interaction in stented blood vessels' |
Year(s) Of Engagement Activity | 2018 |
URL | https://news.liverpool.ac.uk/2018/03/22/faculty-of-science-and-engineering-poster-day-2018-winners/ |
Description | Theme 2: Invited talk. Stereological estimation of canopy surface area. International workshop on Image Analysis and Stereology with applications on Biological and Social Sciences. Santander 11-14 September, 2018 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Theme 2: Invited talk. Stereological estimation of canopy surface area. International workshop on Image Analysis and Stereology with applications on Biological and Social Sciences. Santander 11-14 September, 2018 |
Year(s) Of Engagement Activity | 2018 |
Description | University of Sheffield Physics Department Seminar (6 Feb 2019) Invited Talk (PW) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | This was a dempartmental seminar |
Year(s) Of Engagement Activity | 2019 |
Description | Workshop 4 (T3) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | A workshop is being planned for summer 2017 to engage with policy makers and other stakeholders. The subject of AMR modeling and influenza modeling is a major healthcare topic that is studied at the Liverpool Centre. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.tinyurl.com/EPSRC-LCMH |
Description | workshop 3 (Imaging) jointly with Cambridge CMIH Centre |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | This is a joint event with and held in Cambridge. The teams from all 5 UK centres will be represented, excellent example of UK coherent research efforts in tackling imaging problems. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.turing-gateway.cam.ac.uk/event/tgmw42 |
Description | workshop focused on cell imaging and image analysis |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | The Centre for Cell Imaging organised a 2 day workshop focused on light microscopy techniques and image analysis. 90 researchers and students attended the event mainly from Liverpool and Manchester but also from other Universities in the UK. Industrial partners were invited and the director of the Advanced Imaging Centre at the HHMI Janelia Research Campus, Teng-Leong Chew gave a keynote lecture and a comprehensive hands-on training session on Image Analysis. |
Year(s) Of Engagement Activity | 2017 |
URL | https://cci.liv.ac.uk/2017_workshop.html |