Aims and Fit of Module

The Multi-Agent Systems module is designed to provide students with
a comprehensive understanding of systems composed of multiple
interacting intelligent agents. It aims to equip students with the
theoretical foundations and practical skills necessary to design,
analyze, and implement multi-agent systems. This module is
particularly relevant to students in Information and Computing
Science, Computer Science and Technology, and Mechatronics and
Robotic Systems, as it bridges concepts from artificial
intelligence, distributed systems, and robotics. By exploring topics
such as agent architectures, communication protocols, coordination
strategies, and decision-making processes, students will be prepared
to tackle complex, distributed problems in various domains,
including autonomous robotics, distributed control systems, and
intelligent software applications.

Learning outcomes

A. Critique the concept of an agent, comparing and contrasting it
with other software paradigms such as object-oriented programming,
and analyze the specific characteristics that make certain
applications more suitable for an agent-oriented solution.
B. Assess the key issues involved in constructing agents capable of
intelligent autonomous action, and critically evaluate the main
approaches and methodologies used in the development of such agents.
C. Evaluate the key considerations in designing societies of agents
that can effectively cooperate to resolve problems, including an in-
depth analysis of the different types of multi-agent interactions
possible in these systems.
D. Analyze principal application areas where agent-based solutions
are applied, and demonstrate the ability to develop a functional
agent-based system using a contemporary agent development platform,
showcasing practical proficiency.

Method of teaching and learning

The module will be delivered through a combination of lectures,
tutorials, and private study to provide a balanced and in-depth
learning experience. Lectures will introduce the core theoretical
concepts, models, and frameworks underpinning multi-agent systems,
guided closely by the textbook by Michael Wooldridge. Tutorials will
offer a more interactive environment where students can apply these
concepts to practical problems, discuss case studies, and develop
small-scale agent-based applications using suitable development
tools. These sessions are also intended to encourage collaborative
learning and critical thinking. Students will be expected to engage
in significant private study to review lecture materials, complete
reading assignments, and work on tutorial exercises and project-
based tasks, enabling them to deepen their understanding and develop
the skills necessary for independent problem-solving in multi-agent
system design.