Course Content "Games Theory - Lectures"
1. Introduction to game theory. Game definition, movement order, representation, types of interactions, information content, Nash equilibrium.
2. Elements of utility theory
3. Simultaneous move games. Strategic reasoning: dominance, best response, Pareto optimality, equilibrium, mixing, the Minimax theorem.
4. Simultaneous move games with multiple players.
5. Sequential move games. Applications: strategic moves.
6. Imperfect information games. Applications: signaling games.
7. Repeated games. Stochastic games. Applications: bargaining.
8. Games with incomplete information. Applications: auctions.
9. Normal form games. Algorithms for determining equilibria.
10. Normal form games. Solution concepts: trembling hand perfect equilibrium, rationalizability, evolutionary stable strategies.
11. Game analysis using fuzzy reasoning.
12. Game analysis using genetic algorithms.
13. Graphical interpretation of normal form games. Game analysis using neural networks.
14. Applications of game theory in artificial neural networks and deep learning
Lab Content "Games Theory - Lab"
1. Classification of games.
2. Simultaneous move games. Nash equilibrium. Strategies for simultaneous move games. Minimax theorem.
3. Coordination games. Genetic algorithms.
4. Coordination games. Fuzzy logic.
5. Sequential games. Strategic moves.
6. Election games. Voting.
7. Game theory in artificial neural networks.
