# Introduction To

Game Theory

Algorithmic game theory is an area in the intersection of game theory and computer science, with the objective of understanding and design of algorithms in strategic environments.

We can see Algorithmic Game Theory from two perspectives:

1. Analysis: Which looks at the current implemented algorithms and analyze them using Game Theory tools: calculate and prove properties on their Nash equilibria, price of anarchy, best-response dynamics ...

2. Design: Design games that have both good game-theoretical and algorithmic properties. This area is called algorithmic mechanism design.

# Course Structure

## Game Theory

- Combinatorial Game Theory | Set 1 (Introduction)
- Combinatorial Game Theory | Set 2 (Game of Nim)
- Combinatorial Game Theory | Set 3 (Grundy Numbers/Nimbers and Mex)
- Combinatorial Game Theory | Set 4 (Sprague – Grundy Theorem)
- Minimax Algorithm in Game Theory | Set 1 (Introduction)
- Minimax Algorithm in Game Theory | Set 2 (Introduction to Evaluation Function)
- Minimax Algorithm in Game Theory | Set 3 (Tic-Tac-Toe AI – Finding optimal move)
- Minimax Algorithm in Game Theory | Set 4 (Alpha-Beta Pruning)
- Minimax Algorithm in Game Theory | Set 5 (Zobrist Hashing)
- Variation in Nim Game
- Find the winner in nim-game
- Game of Nim with removal of one stone allowed
- Check if the game is valid or not
- Game of replacing array elements
- Game of N stones where each player can remove 1, 3 or 4
- The prisoner’s dilemma in Game theory
- Choice of Area
- Implementation of Tic-Tac-Toe game
- Optimal Strategy for a Game | DP-31