Computational Game Theory
Semestr: Winter
Range: 2P+2C
Completion:
Credits: 6
Programme type:
Study form: Fulltime
Course language: Czech
Summary:
This course is designed to introduce students to the fundamental concepts and applications of game theory, a powerful tool used to model strategic interactions among individuals, organizations, or countries. Throughout the course, we will delve into various aspects of game theory and explore its wide-ranging applications in diverse fields, including machine learning and AI.
Keywords:
Course syllabus:
1. Introduction. Normal-form games.
2. Nash equilibria for normal-form games.
3. Tractable classes of games. Learning in games.
4. Extensive-form games.
5. Solving imperfect information EFGs.
6. Alternatives to NE.
7. Bayesian games
8. Auctions 1.
9. Auctions 2.
10. Coalitional games. The core.
11. The Shapley value.
12. Weighted voting games.
13. Games in computer science and ML.
14. Summary.
Seminar syllabus:
1. Introduction. Normal-form games.
2. Nash equilibria for normal-form games.
3. Tractable classes of games. Learning in games.
4. Extensive-form games.
5. Solving imperfect information EFGs.
6. Alternatives to NE.
7. Bayesian games
8. Auctions 1.
9. Auctions 2.
10. Coalitional games. The core.
11. The Shapley value.
12. Weighted voting games.
13. Games in computer science and ML.
14. Summary.
Literature:
Shoham, Y. and Leyton-Brown, K.: Multiagent Systems. Cambridge University Press, 2008.
Maschler, M., Zamir, S., and Solan, E. Game Theory. Cambridge University Press, 2020.
Kochenderfer M.J., Wheeler T.A., Wray K.H. Algorithms for decision making. MIT press, 2022.
https://cw.fel.cvut.cz/b231/_media/courses/cgt/cgt_exercises.pdf