Computational Game Theory

Semestr: Winter

Range: 2P+2C

Completion:

Credits: 6

Programme type:

Study form: Fulltime

Course language: Czech

Time table at FEE

Summary:

The course provides an introduction to concepts, models, and algorithms for autonomous agents and multi-agent systems. The first part of the course introduces single-agent models and control architectures; the second part explains key multi-agent models and algorithms, both for cooperative and non-cooperative multi-agent settings. Upon successful completion of the course, students will be able to understand main multi-agent concepts, be able to map real-world multi-agent problems to multi-agent formal models and apply algorithmic techniques to solve them.

Keywords:

Course syllabus:

1. Introduction to multi-agent systems
2. Reactive Agents
3. Belief-Desire-Intention (BDI) architecture
4. Introduction to Game Theory
5. Solving Normal-Form Games
6. Games in Extensive Form
7. Solving Extensive-Form Games
8. Cooperative Game Theory
9. Distributed constraint reasoning 1 (DCSP)
10. Distributed constraint reasoning 2 (DCOP)
11. Social Choice, Voting
12. Resource allocation and Auctions
13. Mechanism Design
14. Wrap-up

Seminar syllabus:

1. Agent architectures
2. Belief-Desire-Intention, Jason
3. Jason
4. Introduction to Game Theory
5. Solving Normal-Form Games
6. Extensive-Form Games
7. Solving Extensive-Form Games
8. Cooperative Game Theory
9. Distributed constraint satisfaction (DCSP)
10. Distributed constraint optimization (DCOP)
11. Social Choice, Voting
12. Introduction to Auctions
13. Auctions, Mechanism Design
14. Wrap-up

Literature:

Shoham, Y. and Leyton-Brown, K.: Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, 2008, ISBN 9780521899437.
Weiss, G. (eds): Multiagent Systems, second edition, MIT Press, 2013
Vidal, J. M.: Fundamentals of Multiagent Systems with NetLogo Examples, 2009

Examiners:

Lecturers:

Instructors: