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The University of Southampton

COMP6203 Intelligent Agents

Module Overview

This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is placed on automated negotiation, cooperation and on-line auctions, and students are required to program a trading agent in Java which will compete in a class tournament within a simulated trading environment.

Aims and Objectives

Module Aims

To give a broad introduction to the new and rapidly expanding field of agent-based computing.

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Motivations for, and appropriate use of, agent-based computing
  • Main agent models in use today and their grounding in artificial intelligence research
  • Main agent decision making frameworks for cooperative and competitive environments
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Deploy an agent within a simulated agent trading environment
  • Analyse and critique the performance of a deployed agent


Topics covered are: Introduction to agent-based computing - Motivations for agent-based computing - Key concepts and models of reasoning (symbolic, reactive and practical) - Rational decision making and handling uncertainty Agent Interactions - Models of coordination (DCOP and the max-sum algorithm) - Models of competitive behaviour (game theory and mechanism design) - Computational markets (auctions) Agent design and implementation - Structuring agent models in code - Deploying agents within a simulated environment - Practical reasoning strategies for computational markets

Learning and Teaching

Completion of assessment task60
Total study time150

Resources & Reading list

Trading Agent Competition - an international forum aiming to encourage and promote high quality research in the technology underlying trading agents..

Gerhard Weiss. Multiagent Systems. 

Michael Wooldrige. An Introduction to MultiAgent Systems. 



MethodPercentage contribution
Examination  (1.5 hours) 60%
Trading agent competition 40%


MethodPercentage contribution
Examination 100%


MethodPercentage contribution
Examination  (1.5 hours) 100%

Repeat Information

Repeat type: Internal & External

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