Twenty20Insight
Lead Research Organisation:
Aston University
Department Name: College of Engineering and Physical Sci
Abstract
As digital technology permeates every area of modern life, we risk becoming over-dependent on complex systems that operate in an opaque way, creating a risk that they exhibit emergent properties that adversely affect their users or their wider environment. This is particularly true as developers increasingly rely on AI or ML techniques as a means to define system behaviour when the problem space is too complex or poorly understood for human developers to explicitly specify that behaviour. We are tackling incompletely understood problems by developing systems whose behaviour and wider impact are by necessity also incompletely understood. This trend, which is largely enabled by an abundance of data harvested from (e.g.) mobile devices, sensors and social media, is radically changing how systems are developed and how they are used. We need a new approach to software engineering that
(i) places greater emphasis on making explicit the risks of unintended behaviour for innovative new software products either through limitations on our understanding of the envisioned product's behaviour or through misuse, and
(ii) actively supports explainability of the exposed behaviour by the running system.
Twenty20Insight is an interdisciplinary project bringing together academic experts in Software Engineering (SE), RE, Design Thinking and ML to help system stakeholders and developers understand and reason about the impact of intelligent systems on the world in which they operate.
(i) places greater emphasis on making explicit the risks of unintended behaviour for innovative new software products either through limitations on our understanding of the envisioned product's behaviour or through misuse, and
(ii) actively supports explainability of the exposed behaviour by the running system.
Twenty20Insight is an interdisciplinary project bringing together academic experts in Software Engineering (SE), RE, Design Thinking and ML to help system stakeholders and developers understand and reason about the impact of intelligent systems on the world in which they operate.
Planned Impact
We expect the project to have a major impact on five classes of beneficiaries beyond the academic research community:
Industrial partners. Twenty20Insight will have an early impact on our industrial partners, with whom we will work to advance the state-of-the-art in stakeholder engagement for the co-design of intelligent systems, and techniques for reasoning about uncertainty and making ML systems' decision-making more transparent.
Early career researchers. The project will provide the attached PDRAs with advanced training in research methods, publication and career development, which will eventually develop the PDRAs into independent researchers by the end of the project.
Research community. Twenty20Insight will develop fundamental new knowledge about engineering intelligent systems both within and at the boundaries between the design, RE/SE, AI and ML research communities.
Industries revolutionised by AI. AI/ML can be applied to nearly every industrial sector. Designing the increasingly complex AI systems requires stakeholders to understand both the Horizon of Possibilities and Envelope of Acceptability when applying ML to their problems. This project has a great potential to tackle such a problem and thus will significantly impact all the industries revolutionised by AI.
Software development companies. The new tools and techniques that will be developed in this project will have the potential to enhance software development companies to meet the increasing demand for intelligent systems operating in an uncertain world.
Wider society. The principal beneficiary of initiatives that aim to generate transformative ideas in order to advance technology, such as the Twenty20Insight project, is ultimately the wider society. This is particularly true of Twenty20Insight since one our explicit aims is to discover techniques to better understand systems' societal impact and enable stakeholders to handle such knowledge in a systematic and transparent way.
Industrial partners. Twenty20Insight will have an early impact on our industrial partners, with whom we will work to advance the state-of-the-art in stakeholder engagement for the co-design of intelligent systems, and techniques for reasoning about uncertainty and making ML systems' decision-making more transparent.
Early career researchers. The project will provide the attached PDRAs with advanced training in research methods, publication and career development, which will eventually develop the PDRAs into independent researchers by the end of the project.
Research community. Twenty20Insight will develop fundamental new knowledge about engineering intelligent systems both within and at the boundaries between the design, RE/SE, AI and ML research communities.
Industries revolutionised by AI. AI/ML can be applied to nearly every industrial sector. Designing the increasingly complex AI systems requires stakeholders to understand both the Horizon of Possibilities and Envelope of Acceptability when applying ML to their problems. This project has a great potential to tackle such a problem and thus will significantly impact all the industries revolutionised by AI.
Software development companies. The new tools and techniques that will be developed in this project will have the potential to enhance software development companies to meet the increasing demand for intelligent systems operating in an uncertain world.
Wider society. The principal beneficiary of initiatives that aim to generate transformative ideas in order to advance technology, such as the Twenty20Insight project, is ultimately the wider society. This is particularly true of Twenty20Insight since one our explicit aims is to discover techniques to better understand systems' societal impact and enable stakeholders to handle such knowledge in a systematic and transparent way.
Publications
Bucchiarone A
(2021)
Agent-Based Framework for Self-Organization of Collective and Autonomous Shuttle Fleets
in IEEE Transactions on Intelligent Transportation Systems
Cámara J
(2022)
The uncertainty interaction problem in self-adaptive systems
in Software and Systems Modeling
Darby A
(2023)
Approaching Unanticipated Consequences
Garcia L
(2024)
Decision Making for Self-Adaptation Based on Partially Observable Satisfaction of Non-Functional Requirements
in ACM Transactions on Autonomous and Adaptive Systems
Garcia-Paucar L, Bencomo N, Sutcliffe A, Sawyer P
(2022)
Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHSCOVID-19 Test and Trace App
Kühn T
(2022)
History-aware explanations
Related Projects
| Project Reference | Relationship | Related To | Start | End | Award Value |
|---|---|---|---|---|---|
| EP/T017627/1 | 31/08/2020 | 30/08/2021 | £586,520 | ||
| EP/T017627/2 | Transfer | EP/T017627/1 | 30/09/2021 | 13/07/2024 | £390,864 |
| Description | In Twenty20Insight, we are tackling the need for software engineering techniques that: (i) places greater emphasis on making explicit the risks of unintended behaviour for innovative new software products either through limitations on our understanding of the envisioned product's behaviour or through misuse, and (ii) actively supports explainability of the exposed behaviour by the running system. Let's remember the objectives to describe to what extent have the award objectives met so far: O1: stakeholders are able to explore how envisioned systems might interact with and impact on the external world in which they will operate - to explore the horizon of possibilities (HoP) and define the Envelop of Acceptability (EoA); [WP1,WP2] O2: developers can model and reason about the uncertainty that is an inevitable residual feature of the system design, even after the definition of the EoA; [WP1,WP2 and WP3] O3: advance the extent to which ML algorithms behave can be rendered interpretable by humans [W3 and WP4, WP5] Twenty20Insight started in September 2020 (in the middle of the pandemic). Since then, even with the challenges posed by the pandemic, we have been able to work of different collaborations and publications towards the 3 goals. We have the following achievements and findings: a. Techniques for the quantification of the impact of values on requirements and software engineering (O1, WP2, WP3). 2 Conference Publications and a workshop publications. b. The technique and software architecture (Pri-AwaRE) to create runtime awareness about priorities of quality properties (i.e. how much value is given to a property) and measure degrees of uncertainty to support autonomous decision-making (O2, O3, WP3, WP4, WP5) 1 journal publication, 2 conference publication, 1 Exemplar. c. Techniques (ETeMoX, Cronista) for the explanation of autonomous systems based on ML/AI (O2, O3, WP3,WP4). 2 journal publications, 4 conference publications d. First steps towards incorporating speculative techniques in Requirements Engineering to better anticipate unwanted emergent behaviour in uncertain environments. (O1, WP1, WP2). 1 Conference paper under submission, 2 workshops delivered to the industry partners. 2 workshops in the next two weeks. |
| Exploitation Route | Based on our collaborations and product with the Industry partners In the international conferences REFSQ and RE (we have created a workshop to run, which was accepted) |
| Sectors | Digital/Communication/Information Technologies (including Software) |
| URL | https://cs.aston.ac.uk/Twenty20Insight/ |
| Description | We have taken the first steps towards incorporating speculative techniques in Requirements Engineering to better anticipate unwanted emergent behaviour in uncertain environments. The process has been used in the delivery of a couple of workshops with our Industry partners. We hope to have concrete results in the second stage of the project. |
| First Year Of Impact | 2022 |
| Sector | Digital/Communication/Information Technologies (including Software) |
| Impact Types | Cultural Societal Economic |
| Description | Requirements Models for Artificial Intelligence (ReqModAI): Framework and Case study |
| Amount | £4,991 (GBP) |
| Funding ID | RF090115 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 05/2022 |
| End | 06/2022 |
| Title | RDMSim: An Exemplar for Evaluation and Comparison of Decision-Making Techniques for Self-Adaptation |
| Description | To enable researchers to evaluate and compare decision-making techniques for self-adaptation, we present the RDMSim exemplar. RDMSim enables researchers to evaluate and compare techniques for decision-making under environmental uncertainty that support self-adaptation. The focus of the exemplar is on the domain problem related to Remote Data Mirroring, which gives the opportunity to face the challenges described above. RDMSim provides probe and effector components for easy integration with external adaptation managers, which are associated with decision-making techniques and based on the MAPE-K loop. Specifically, (i) RDMSim, a simulator for real-world experimentation, (ii) a set of realistic simulation scenarios that can be used for experimentation and comparison purposes, (iii) data for the sake of comparison. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | The RDMSim exemplar presented is implemented in Java, keeping in view the operational model presented in [1], [2]. It simulates the RDM presenting a fully connected network of mirrors. The simulator offers the flexibility of changing the number of mirrors to create a customized RDM network according to the experiment's requirements. Additionally, we provide an implementation of different scenarios that define possible different uncertain environmental contexts for the RDM [20]. A Python version is also publicly available. Researchers can use these scenarios to test their specific decision-making techniques based on Reinforcement Learning [21], Multi-Criteria Decision Analysis [22] and Evolutionary Computation [3] among others. Researchers can also design their own scenarios by modifying the different parameter ranges. [1] M. Ji, A. C. Veitch, J. Wilkes et al., "Seneca: remote mirroring done write." in USENIX Annual Technical Conference, General Track, 2003, pp. 253-268. [2] K. Keeton, C. Santos, D. Beyer, and J. Chase J.and Wilkes, "Designing for disasters," USENIX Conference on File and Storage Technologies, Berkeley, 2004. [20] N. Esfahani, E. Kouroshfar, and S. Malek, "Taming uncertainty in self-adaptive software," in Proceedings of the 19th ACM SIGSOFT symposium and the 13th European Conference on Foundations of software engineering - SIGSOFT/FSE '11. Szeged, Hungary: ACM Press, 2011, p. 234. [21] H. Samin, L. Garcia Paucar, B. Nelly, and P. Sawyer, "Towards priority awareness in autonomous intelligent systems," in 36th ACM/SIGAPP Symposium On Applied Computing (SAC). ACM, 2021. [22] E. Triantaphyllou, "Multi-criteria decision-making methods," in Multicriteria decision making methods: A comparative study. Springer, 2000, pp. 5-21. |
| URL | https://zenodo.org/record/4613152#.YjJkHZPP0qw |
| Description | EPSRC IAA: WeDecide: Clinical Tool For Shared Decision-Making For Treatment Of Menopause Symptoms |
| Organisation | NHS England |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | 10 per cent of women leave the workforce due to menopause, while one in four considers leaving. The weDecide project aims to evaluate a novel technique to support personalised and shared decision-making (PSDM) for menopause treatment that considers not just the criteria of a menopause expert but also that of the woman experiencing the peri-menopausal symptoms. The technique builds on the decision-making AI-based tool developed in the EPSRC project Twenty20Insight, which considers the priorities/preferences of humans. weDecide is based on outcomes of the EPSRC project Twenty20Insight[*], and the EPSRC seedcorn projects ReqModAI[**] and iDecide[***], led by Dr Bencomo. These projects focussed on developing AI-based techniques for autonomous decision-making under uncertainty. Crucially, iDecide allowed us to make initial steps towards using AI for Personalised and Shared Decision-Making (PSDM) [NHS1] in Digital Health. |
| Collaborator Contribution | weDecide focuses on assessing the clinical relevance and acceptability of the decisions prompted by the weDecide Tool to inform an EPSRC bid. The NHS GP offers us her expertise in Menopause. |
| Impact | No outputs have been delivered yet as the collaboration has just started. |
| Start Year | 2024 |
| Description | SRF: Just Transitions To A Net Zero World (Strategic Research Funding Project funded by Durham) |
| Organisation | Durham University |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | https://www.durham.ac.uk/research/institutes-and-centres/csdlp/justn0w/ As part of this collaboration, my contributions are primarily centered on shaping the research agenda, attracting key talent, and fostering interdisciplinary integration between Computer Science and Law (plus Bioscience and Economics). My previous work in EPSRC Twenty20Insight is now informing the research direction and methodologies applied in JusTN0W. 1. JusTN0W - Just Transitions to a Net Zero World My role has been instrumental in defining the AI-driven decision-making methodologies that will support sustainable transitions. I have been actively involved in recruiting and building a team of Computer Science researchers who will apply their expertise in AI, optimization, and uncertainty modeling to real-world legal and environmental challenges. The project aims to bridge the gap between computational methods and legal frameworks, ensuring that policy and regulatory decisions benefit from data-driven insights. The methodologies developed in Twenty20Insight-particularly in decision-making under uncertainty and AI-assisted analytics-are now being adapted and expanded within JusTN0W to address sustainability policy and regulation. 2. EPSRC Twenty20Insight Influence on JusTN0W Twenty20Insight, which concluded last year, provided foundational research on AI-driven decision-making under uncertainty, particularly in risk-aware autonomous systems. The insights from this project are now being applied to sustainability challenges, where legal and policy decisions require robust, data-driven support. The computational tools and uncertainty quantification techniques developed in Twenty20Insight are being refined to align with the needs of legal frameworks, contributing to JusTN0W's efforts in just transitions and Net Zero strategies. Through this collaboration, we are hiring and integrating Computer Science researchers into legal and environmental applications, facilitating a cross-disciplinary knowledge exchange that will drive JusTN0W forward. The focus ahead is on building computational models, refining decision-support tools, and ensuring AI applications align with legal and policy considerations for sustainable decision-making. |
| Collaborator Contribution | 2. EPSRC Twenty20Insight Influence on JusTN0W Twenty20Insight, which concluded last year, provided foundational research on AI-driven decision-making under uncertainty, particularly in risk-aware autonomous systems. The insights from this project are now being applied to sustainability challenges, where legal and policy decisions require robust, data-driven support. The computational tools and uncertainty quantification techniques developed in Twenty20Insight are being refined to align with the needs of legal frameworks, contributing to JusTN0W's efforts in just transitions and Net Zero strategies. Through this collaboration, we are hiring and integrating Computer Science researchers into legal and environmental applications, facilitating a cross-disciplinary knowledge exchange that will drive JusTN0W forward. The focus ahead is on building computational models, refining decision-support tools, and ensuring AI applications align with legal and policy considerations for sustainable decision-making. |
| Impact | Not yet. |
| Start Year | 2023 |
| Description | Human-Machine Teaming for Shared Decision-Making under Uncertainty |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | A talk presented in the Turing Workshop on Human-Centric Artificial and Computational Intelligence organised by Prod Federica Sarro (UCL) and Dr Ke Li (Exeter). A EPSRC bid is being led by me with Dr K Li (Exeter) and Prof Yulan He (KCL) and it was triggered by that presentation. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://colalab.ai/turing_workshop/ |
| Description | Invitation to talk at CS Department, Birmingham University - Seminars of CS Department (March 2020) - Online due to Pandemic |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Postgraduate students |
| Results and Impact | Invitation to talk at CS Department, Birmingham University - Seminars of CS Department (March 2021) Seminar for Academics and Postgraduate Students |
| Year(s) Of Engagement Activity | 2021 |
| Description | Invitation to talk at CS Department, Durham University - Seminars of CS Department (April 2020) - Online due to Pandemic |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | Invitation to talk at CS Department, Durham University - Seminars of CS Department (April 2021) |
| Year(s) Of Engagement Activity | 2021 |
| Description | Invitation to talk at CS Department, Leeds University - Seminars of CS Department (February 2022) - Online due to Pandemic |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Postgraduate students |
| Results and Impact | The Seminar was for a cohort of 100 postgraduate students (talk online). |
| Year(s) Of Engagement Activity | 2022 |
| Description | Modelling Human-Machine Teaming for Shared Decision-Making under Uncertainty |
| 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 | Keynote given in the Modellierung 2024 Cinference in Germany. https://scholar.google.co.uk/citations?view_op=view_citation&hl=en&user=86H7HmkAAAAJ&sortby=pubdate&citation_for_view=86H7HmkAAAAJ:1lhNe0rCu4AC |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://bpt.hpi.uni-potsdam.de/modellierung2024/keynotes/ |
| Description | Participation in an activity, workshop or similar - Seminar Model Hybridization for Digital Twins - https://www.bellairs2025.ece.mcgill.ca/schedule.htm - Feb 2025 |
| 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 | The 1st 1-Week Workshop on Model Hybridization for Digital Twins at the Bellairs Research Institute of McGill University in Holetown, Barbados, is taking place from Friday, February 21st, 2025 to Friday, February 28th, 2025 with a special emphasis on the use of different forms of models (e.g., analytical models and machine learning models) in the context of digital twins. Digital twins promise tremendous potential for gaining insights, optimize operations, and improve decision-making for cyber-physical systems across various industries, including manufacturing, healthcare, transportation, and more. Recent developments show that MDE can play a central role in systematically leveraging the potential of digital twins, and many researchers from the MDE community have applied MDE technology to build digital twins in recent years. In the future, the predictive capabilities of digital twins will be leveraged for dynamically evolving eco-systems to address challenges such as sustainability at a much more complex scale. To this aim, techniques for the coordinated use of heterogeneous descriptive and prescriptive models need to be elaborated, and the propagation of uncertainty across digital twin boundaries investigated, leading towards the definition of interfaces for DT composition and a unifying theory for inductive and deductive reasoning. The modelling-related Bellairs workshop series have traditionally had a strong focus on software composition and modularity (aspect-oriented modelling (2010, 2011, 2012, 2013), concern-oriented modelling (2015, 2017), interfaces for software reuse (2018), polyglotism (2023), digital twins composability (2024)), but also on the interplay of data and models (data and models (2019, 2020), feedback-driven decision making (2022)). We therefore want to dedicate the upcoming Bellairs workshop on investigating the hybridization of different forms of models (e.g., analytical models, architecture models, machine learning models) for digital twins. The workshop was highly interactive and open-minded, with the main objective to reflect on the combination of different forms of models in complex scenarios for digital twins. At least a publication is under way. |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://www.bellairs2025.ece.mcgill.ca/schedule.htm |
| Description | Seminar 4th Winter Modeling Meeting - https://wmm25.notion.site/4th-Winter-Modeling-Meeting-120f3eb8c00f815f9a8cc3ef502b358f. Feb 2025 |
| 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 | I attended this event to contribute insights from my research in Twenty20Insight, particularly on decision-making under uncertainty and the adaptability of software systems. Modern software-based systems must continuously adapt to dynamic environments, blurring the boundary between engineering-time and execution-time. My work in Twenty20Insight explored how AI-driven decision-making can enhance temporal adaptability, allowing systems to evolve in response to changing conditions, much like human cognition. A key challenge is managing abstractions, which enable both cognitive flexibility for users and scalability for systems. Software engineering must now focus on Abstraction Engineering-developing dynamic, context-aware abstractions that balance complexity reduction with real-time adaptability. My contribution to the event highlighted how AI-driven models, uncertainty quantification, and adaptive decision-making from Twenty20Insight can inform new approaches to software adaptability, ensuring that abstractions evolve alongside changing requirements. (For a more detailed discussion, see: https://arxiv.org/pdf/2408.14074). |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://wmm25.notion.site/4th-Winter-Modeling-Meeting-120f3eb8c00f815f9a8cc3ef502b358f |
| Description | Workshop on Design Thinking for Arcadis |
| 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 | Arcadis Airport Design Futures workshop 1. Longer-term horizon 2035 Inputs are background research on future air travel visions, technology development, passenger attitude and experience surveys. The outputs were illustrated scenarios of future air travel / airport experience focus, and a report on implications for investment decisions, cross referenced to a range of alternative scenarios. Participants: ARCADIS clients (airport managers, executives), other interested parties- Airlines, travel/holiday vendors, UK Government- civil servants. Aims: (i) to explore the horizon of possibilities in future air travel and develop a range of visions to illustrate possible futures as videos, VR, MURAL demos, etc (ii) to develop evaluation criteria and use these to critique future visions to inform policy of passenger experience/marketing and investment decisions in airport facilities |
| Year(s) Of Engagement Activity | 2021 |
| Description | keynote at Modellierung 2024 in Germany |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Models for Human-Machine Teaming for Shared Decision-Making under Uncertainty There is growing uncertainty about the runtime environment of software systems. Therefore, how the system should behave under different contexts cannot be fully predicted at design time. It is considerations such as these that have led to the development of self-adaptive systems (SAS), which can dynamically and autonomously reconfigure their behaviour to respond to changing external conditions. The use of Machine Learning (ML) and AI has exacerbated the issues by adding more uncertainty sources. The scope of the talk is in the areas of Model-driven Engineering (MDE), Requirements Engineering (RE), software engineering (SE), and the development of techniques to quantify uncertainty to improve decision-making. The explicit treatment of uncertainty by the running system improves its judgment to make decisions supported by evaluating evidence found during runtime, possibly including the human-in-the-loop. The speaker will discuss how quantification of uncertainty can improve requirement elicitation (using simulations, for example). The talk will also cover different approaches to quantifying uncertainty, models@run.time and their role in Human-Machine Teaming. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://bpt.hpi.uni-potsdam.de/modellierung2024/keynotes/ |
| Description | keynote at the 15th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2025) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Title: Bayesian Theory of Surprise to Quantify Degrees of Uncertainty Location: ICPRAM 2025 Date: 25/02/2025 In software engineering for self-adaptive systems (SASs), we are witnessing a growing intersection between Artificial Intelligence (AI) and Software Engineering (SE)-and we are just getting started! This talk is based on work in progress, which I have been developing in deep collaboration with Huma Samin and Amel BELAGGOUN and, more recently, Dylan Walton. I am incredibly grateful for their contributions and insights-this work would not be possible without them! In this talk, I will introduce a novel Bayesian definition of Surprise as a quantitative tool to measure uncertainty and deviations from expected behavior. Surprise is a powerful mechanism that helps systems determine when observed data challenges prior assumptions-enabling them to adapt accordingly or flag anomalies. We will explore applications of the Bayesian Theory of Surprise in self-adaptive systems, leveraging Bayesian Inference and Partially Observable Markov Decision Processes (POMDPs). Additionally, I will discuss different Surprise-based approaches to quantifying uncertainty, including: ? Bayesian Surprise ? Shannon Surprise ? Bayes Factor Surprise ? Digital Twins and their role in adaptive decision-making |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://icpram.scitevents.org/KeynoteSpeakers.aspx?y=2025 |
| Description | webinar 'Navigating the Future with Digital Twins' in collaboration with ACM India -October 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Presentation about the role of abstraction and AI in Digital Twins. in collaboration with ACM India and Tata Consultancy Services https://www.linkedin.com/posts/tcs-research_fireside-tcsresearch-inventingforimpact-activity-7241403752765648896-j3zF?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAAHyi6YB20LaL1A7YoWaLgJeeFy9u7gSLUI |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.linkedin.com/posts/tcs-research_fireside-tcsresearch-inventingforimpact-activity-7241403... |