AI Toolbox - Search Algorithms, Min-Max Game, and CSP Solver

Introduction

Welcome to the AI Toolbox, a project that combines various AI algorithms to provide visualization and functionality for search algorithms, a game (CONNECT4) using min-max algorithms, and a Constraint Satisfaction Problem (CSP) solver. This toolbox aims to provide a comprehensive understanding of these AI techniques through interactive visualizations and practical examples.

Features

1.Search Algorithm Visualization

The toolbox offers a visualization module that allows you to explore and understand various search algorithms. It includes the following algorithms:

Depth-First Search (DFS) Breadth-First Search (BFS) Uniform-Cost Search (UCS) A* Search Depth-Limited Search Iterative Deepening Search Hill-Climbing Search Min-Max Search

2. Min-Max Game

The AI Toolbox also includes a game module that utilizes the min-max algorithm. This module allows you to play a game against an AI opponent. The game is called Connect Four. The AI opponent utilizes the min-max algorithm to make intelligent decisions, providing a challenging and interactive experience.

3. CSP solver

The CSP solver module within the toolbox enables you to solve complex constraint satisfaction problems. It employs the CSP algorithm to find solutions for problems involving variables, domains, and constraints. You can input your own problem instances or use predefined examples to explore and analyze the CSP solving process.

Contributors

The AI Toolbox project has benefited from the contributions and efforts of the following individuals:

We would like to express our sincere appreciation for their valuable contributions, including code contributions, bug fixes, feature suggestions, and documentation improvements. Their dedication has played a crucial role in enhancing the functionality and usability of the AI Toolbox.

Contributions and Feedback

Contributions to the AI Toolbox project are welcome! If you encounter any issues, have ideas for improvements, or would like to contribute new features, please submit a pull request on our GitHub repository. We appreciate your feedback and suggestions for enhancing the toolbox.

Acknowledgments

We would like to express our gratitude to the open-source community for providing valuable resources, algorithms, and libraries that made the AI Toolbox possible. We also extend our thanks to the users and contributors who have helped improve the toolbox through their feedback and suggestions.