Collective decision making in distributed systems

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.