Collective decision making in distributed systems

Lead Research Organisation: University of Bristol
Department Name: Mathematics

Abstract

The project falls with the following EPSRC research areas: (1) ICT networks and distributed systems, and (2) Statistics and applied probability.

Collective decision-making is widespread amongst biological organisms ranging from bacteria to social insects such as ants and bees (where colonies make collective decisions about foraging and nest sites) to human beings (from consumers to stock market traders). The need for collective decision-making also arises in engineered systems such as the Internet, and power and transport networks, which are composed of large numbers of autonomous entities that need to coordinate route choice or supply and demand decisions. Newer applications include swarm robotics and blockchain technologies.

In this project, we will explore a number of simplified mathematical models of collective decision-making and study the emergent phenomena that arise when they are employed by large numbers of interacting autonomous agents. As an example, suppose agents receive independent private signals about a state of nature, and have a shared goal of inferring the true state of nature. The most efficient solution is to pool all the information and use it to make the inference, but the system may be too large for this to be feasible. Can agents cooperate using only limited communication with neighbours to achieve inference that is comparable to what could be achieved with full information sharing? We will address such questions using a combination of rigorous mathematical analysis and simulations. We will propose and analyse a variety of algorithms for collective decision-making problems with well-posed objectives.

Planned Impact

The COMPASS Centre for Doctoral Training will have the following impact.

Doctoral Students Impact.

I1. Recruit and train over 55 students and provide them with a broad and comprehensive education in contemporary Computational Statistics & Data Science, leading to the award of a PhD. The training environment will be built around a set of multilevel cohorts: a variety of group sizes, within and across year cohort activities, within and across disciplinary boundaries with internal and external partners, where statistics and computation are the common focus, but remaining sensitive to disciplinary needs. Our novel doctoral training environment will powerfully impact on students, opening their eyes to not only a range of modern technical benefits and opportunities, but on the power of team-working with people from a range of backgrounds to solve the most important problems of the day. They will learn to apply their skills to achieve impact by collaborative working with internal and external partners, such as via our Rapid Response Teams, Policy Workshops & Statistical Clinics.

I2. As well as advanced training in computational statistics and data science, our students will be impacted by exposure to, and training in, important cognate topics such as ethics, responsible innovation, equality, diversity and inclusion, policy, effective communication and dissemination, enterprise, impact and consultancy skills. It is vital for our students to understand that their training will enable them to have a powerful impact on the wider world, so, e.g., AI algorithms they develop should not be discriminatory, and statistical methodologies should be reproducible, and statistical results accurately and comprehensibly communicated to the general public and policymakers.

I3. The students will gain experience via collaborations with academic partners within the University in cognate disciplines, and a wide range of external industrial & government partners. The students will be impacted by the structured training programmes of the UK Academy of Postgraduate Training in Statistics, the Bristol Doctoral College, the Jean Golding Institute, the Alan Turing Institute and the Heilbronn Institute for Mathematical Sciences, which will be integrated into our programme.

I4. Having received an excellent training, the students will then impact powerfully on the world in their future fruitful careers, spreading excellence.

Impact on our Partners & ourselves.

I5. Direct impacts will be achieved by students engaging with, and working on projects with, our academic partners, with discipline-specific problems arising in engineering, education, medicine, economics, earth sciences, life sciences and geographical sciences, and our external partners Adarga, the Atomic Weapons Establishment, CheckRisk, EDF, GCHQ, GSK, the Office for National Statistics, Sciex, Shell UK, Trainline and the UK Space Agency. The students will demonstrate a wide range of innovation with these partners, will attract engagement from new partners, and often provide attractive future employment matches for students and partners alike.

Wider Societal Impact

I6. COMPASS will greatly benefit the UK by providing over 55 highly trained PhD graduates in an area that is known to be suffering from extreme, well-known, shortages in the people pipeline nationally. COMPASS CDT graduates will be equipped for jobs in sectors of high economic value and national priority, including data science, analytics, pharmaceuticals, security, energy, communications, government, and indeed all research labs that deal with data. Through their training, they will enable these organisations to make well-informed and statistically principled decisions that will allow them to maximise their international competitiveness and contribution to societal well-being. COMPASS will also impact positively on the wider student community, both now and sustainably into the future.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023569/1 01/04/2019 30/09/2027
2741510 Studentship EP/S023569/1 01/10/2022 18/09/2026 Xinrui Shi