Course Description
We will learn the main game theory concepts and ideas from practice and use cases. We will consider the classical strategic situations and decision-making in complex situations and how game theory proposes to deal with them. Then we apply ideas to real problems and implement some of them with algorithms. Topics:- Games in strategic and extensive forms
- Nash equilibrium and its calculation
- Backward induction, games with perfect, imperfect, and incomplete information
- Repeated games, cooperative games, evolutionary games.
Course tools
- Python (NashPy, Axelrod)
Prerequisites
- General probability
- Basic calculus
- Algorithms