This project implements an AI for the game of Halma using the Minimax algorithm with Alpha-Beta pruning. The AI plays on a 16x16 board, aiming to move all pieces to the opponent's starting camp. It supports human vs AI and AI vs AI modes, with adaptive strategies based on game phases.
- Minimax Algorithm: Evaluates possible moves to choose the best one.
- Alpha-Beta Pruning: Optimizes Minimax by reducing the number of nodes evaluated.
- Heuristics:
- Closest to Opponent Camp: Encourages pieces to move toward the opponent's camp.
- Most Moves: Favors positions with more possible moves.
- Pawn Clustering: Encourages pieces to stay close together.
- Adaptive Strategies: AI adjusts strategies based on the game phase (early, mid, late).
- Human vs AI Mode: Play against the AI in the console.
- Tournament Mode: Run AI vs AI matches to test strategies.