Multi agent systems and collective behaviour

A multi-agent system (MAS) consists of a number of autonomous agents interacting with each other and with their environment. MAS is one of the fastest-growing areas of AI and a very general paradigm to understand many complex natural phenomena, such as the behaviour of ant colonies, fish swarms and human groups. Conversely, MAS approaches are crucial in the design of some of the most cutting-edge AI and cyber-physical systems, such as swarm robots. Hybrid cyber-physical systems, in which natural and artificial agents interact, represent the third important form of MAS. The internet, where millions of humans and computational agents interact in intricate and complex ways, is the paradigmatic example of such a hybrid.

This highly interdisciplinary unit discusses the most important methods to describe, analyse and design MAS and discusses their practical applications in scientific modelling and artificial intelligence.

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.