Introductory description

Agent-based systems offer a new paradigm for computer science, based around a strong theoretical foundation and with a large number of practical deployed applications.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Overview: definitions of agents, distributed AI and agents, intelligent agents, multi-agent systems, cooperation, agent application areas.

Logic-based agents: actions, goals and strategies.

Decision-making agents: expected utility and decisions.

Game-theoretic agents: equilibria and rationality.

Learning-agents: Markov Decision Processes, policy approximation and opponent modelling.

Social-agents: Cooperative decision-making, matching and networks.

Learning outcomes

By the end of the module, students should be able to:

• Students will learn the basic methodologies for the design and the analysis of multi-agent systems, in competitive and cooperative interaction, both from the theoretical and the practical point of view.

Indicative reading list

Please see Talis Aspire link for most up to date list.

View reading list on Talis Aspire

Subject specific skills

Logical reasoning;
Problem Solving;

Transferable skills

Problem Solving;
Logical reasoning;
Self-directed learning.