A C++ game-playing bot that uses the Minimax algorithm with Alpha-Beta Pruning to efficiently evaluate and play TicTacToe and Connect Four. This project was built to explore decision trees, game theory, and basic AI optimization.
- Plays TicTacToe and Connect Four against a human
- Uses a recursive Minimax algorithm to evaluate best moves
- Implements Alpha-Beta Pruning to skip irrelevant branches and speed up search
- Evaluates win/loss/tie states and dynamically searches based on board size
- Game Trees: Simulates future moves and outcomes by recursively evaluating board states
- Minimax: Chooses moves that maximize the AI's chance of winning while minimizing the opponent's
- Alpha-Beta Pruning: Optimizes Minimax by skipping branches that won’t influence the outcome
- Implementing recursive algorithms cleanly in C++
- Applying pruning logic to dramatically reduce search space
- Modeling turn-based board games in memory
- Balancing evaluation depth and runtime (especially in Connect Four)