Computational Game Theory
Code | Completion | Credits | Range | Language |
---|---|---|---|---|
BE4M36MAS | Z,ZK | 6 | 2P+2C | English |
- The course cannot be taken simultaneously with:
- Computational Game Theory (B4M36MAS)
- The course is a substitute for:
- Computational Game Theory (B4M36MAS)
- Lecturer:
- Branislav Bošanský, Michal Pěchouček (guarantor), Michal Jakob, Tomáš Kroupa
- Tutor:
- Branislav Bošanský, Michal Pěchouček (guarantor), Aditya Ajit Aradhye, David Fiedler, Michal Jakob, Tomáš Kroupa, Dominik Andreas Seitz, Michal Šustr, Tomáš Votroubek
- Supervisor:
- Department of Computer Science
- Synopsis:
-
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.
- Requirements:
- Syllabus of lectures:
-
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
- Syllabus of tutorials:
-
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
- Study Objective:
- Study materials:
-
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
- Note:
- Further information:
- https://cw.fel.cvut.cz/wiki/courses/BE4M36MAS
- Time-table for winter semester 2021/2022:
-
06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon Tue Wed Thu Fri - Time-table for summer semester 2021/2022:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Open Informatics - Artificial Intelligence (compulsory course of the specialization)