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Multi-agent Systems2024HT
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Course plan
No of lectures
TBD
Recommended for
All PhD students in computer science and related subjects.
The course was last given
Fall 2023
Goals
The overall aim of the course is to give an overview of multiagent systems and
in depth knowledge of some areas of multiagent systems. After the course
students should be able to:
- List and explain important problems and techniques in the area of multiagent
systems.
- Explain how central algorithms in the area of multiagent systems work.
- Be able to implement some central algorithm in the area of multiagent
systems.
- Evaluate and apply different game theoretic approaches.
- Design and use auctions for allocating resources in a multiagent system.
Prerequisites
An introductory AI course, knowledge of programming, probabilities, and logic.
Organization
Lectures, seminars, and labs.
Content
* Architectures for multiagent systems
* Distributed AI, including distributed constraint satisfaction and
optimization
* Game theory, including normal form and extensive form games
* Communication, including speech acts
* Aggregated preferences, including voting
* Auctions for multiagent resource allocation
* Multiagent decision-making, including task allocation
Literature
Shoham, Yoav and Leyton-Brown, Kevin, (2009) Multiagent systems - Algorithmic, Game-Theoretic and Logical Foundations Cambridge University Press. ISBN: 978-0-521-89943-7
Lectures
TBD
Examination
Exercises, 4 ECTS
Labs, 2 ECTS
Examiner
Fredrik Heintz or Daniel de Leng (TBD)
Credits
6 ECTS
Comments
Page responsible: Director of Graduate Studies
