Minimax Algorithm

AI decision-making for Tic-Tac-Toe using Minimax with Alpha-Beta Pruning optimization

🎮 How to Play

  • • Click cells on the board to play as X (human)
  • • AI (O) automatically plays after your move
  • • Click "AI Move" button to force AI move when it's AI's turn
  • • Click "Hint" button to see the best move suggestion
  • • Switch to Tree View to see algorithm exploration
  • • Click tree nodes to inspect board states
  • • Use animation controls to watch tree building
  • • Try Alpha-Beta Pruning for efficiency comparison

🧠 About Minimax

Minimax is a decision-making algorithm for adversarial games. It explores all possible moves, assuming both players play optimally. Alpha-Beta Pruning optimizes by eliminating branches that won't affect the final decision, significantly reducing computation.

🔗 Related Algorithms

Coming soon: A* Pathfinding, Genetic Algorithms, Monte Carlo Tree Search