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
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Main agent decision making frameworks for cooperative and competitive environments
- Motivations for, and appropriate use of, agent-based computing
- Main agent models in use today and their grounding in artificial intelligence research
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
Syllabus
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 cooperation
- 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
| Type | Hours |
|---|---|
| Tutorial | 4 |
| Lecture | 24 |
| Completion of assessment task | 60 |
| Revision | 50 |
| Practical | 12 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Gerhard Weiss. Multiagent Systems.
Y. Shoham and K. Leyton-Brown. Multiagent Systems.
Michael Wooldrige. An Introduction to MultiAgent Systems.
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Continuous Assessment | 40% |
| Class Test | 10% |
| Final Assessment | 50% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat Information
Repeat type: Internal & External