Minimax Simulator with Alpha-Beta Pruning

Minimax algorithm is used with Alpha-beta pruning in programming.

Table of Contents

• Minimax Simulator with Alpha-Beta Pruning
  • Table of Contents
  • Introduction
  • Features
  • Usage
  • How It Works
  • Contributing
  • License

Introduction

The Minimax Simulator is a project that demonstrates the Minimax algorithm with Alpha-beta pruning. The Minimax algorithm is a decision-making algorithm used in artificial intelligence and game theory. Alpha-beta pruning is an optimization technique for the Minimax algorithm that reduces the number of nodes evaluated in the search tree.

Features

• Implementation of the Minimax algorithm with Alpha-beta pruning.
• Visual representation of the algorithm.
• Interactive user interface.

Usage

You can use the Minimax Simulator live at Minimax Simulator.

How It Works

The Minimax algorithm with Alpha-beta pruning works as follows:

1. Minimax Algorithm: The algorithm evaluates all possible moves in a game to determine the best move for the player. It assumes that the opponent will also play optimally.
2. Alpha-Beta Pruning: This optimization technique reduces the number of nodes evaluated in the search tree by eliminating branches that cannot influence the final decision.

Contributing

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.