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Subsections
Here are links to the
course home page
and
the formal TQA
description.
The aim of this course is to provide a comprehensive introduction to
agents and multiagent systems. It covers a broad range of distributed
artificial intelligence topics including agent architectures, agent
interaction and communication, and applications of agent-based
systems. It lays the foundations for advanced courses such as
Multi-Agent Semantic Web Systems.
- Basics:
definitions of agency;
properties of agents;
agents vs. objects.
- Agent Architectures:
reactive/deliberative/hybrid agents;
BDI and practical reasoning agents;
deductive reasoning agents.
- Rational Reasoning:
decision-theoretic/game-theoretic foundations;
bounded rationality;
means-ends reasoning.
- Interaction:
non-communicative interaction;
agent communication languages;
interaction protocols.
- Agent coordination:
distributed problem solving, planning and task sharing;
teamwork and coalition formation;
negotiation (game-theoretic/heuristic/argumentation-based);
matchmaking and brokering.
- Advanced Topics:
distributed search/distributed constraint satisfaction;
multiagent learning;
agent-oriented software engineering;
trust/norms/institutions, organisational approaches.
Two practical programming and/or written pencil-and-paper assignments.
References:
* Michael J. Wooldridge. An Introduction to Multiagent Systems, John Wiley and Sons, 2002
* G. Weiss (ed.). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 1999
* A more detailed reading list will be provided for individual topics
Next: AI Large Practical
Up: Descriptions of Courses and
Previous: Descriptions of Courses and
Contents
Colin Stirling
2006-01-05