A Lecture on Game Theory

Hi @jstac,

I think a lecture on game theory can connect our lectures (linear programming and Markov chain) and computational aspects of economics naturally. It is a preliminary idea, but I think the content is enough for a lecture.

We can structure the lecture into the following:

1. Introduction: Actions and Payoffs
2. Strategic-form games -- Nash equilibrium, dominance, and mixed strategies
3. Extensive-form games -- Game tree, backward and forward induction, and subgame-perfect nash equilibrium
4. Potential Extensions: Incomplete information (Bayesian game), stochastic game, correlated equilibria, repeated game, and auctions

Within the lecture, we can tie game theory with linear programming. We can use example games in quantecon.py as examples.

Here is a good resource that can help us to structure the lecture and link to the computational side of game theory: https://www.cs.cmu.edu/~sandholm/cs15-892F13/algorithmic-game-theory.pdf

Please kindly let me know if you think it is a good lecture to be added, and if there is anything else that we can add to the discussion. Please feel free to invite other team members to the discussion if you think this lecture is worth adding.

Many thanks in advance.