Pacman Game Automation with AI This project involves the development of an AI-driven Pacman game, leveraging advanced algorithms to automate gameplay and enhance decision-making capabilities.

Key Features Minimax Algorithm with Alpha-Beta Pruning: Implemented the Minimax algorithm for optimal decision-making, utilizing Alpha-Beta pruning to significantly reduce the search space and improve computational efficiency. Breadth-First Search (BFS) Algorithm: Integrated BFS for effective pathfinding and maze navigation, enabling the Pacman to traverse the game environment intelligently.