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https://github.com/kishanvyas308/ai-mini-projects

This repository contains a collection of AI-based mini projects. Each project demonstrates the application of different AI algorithms and techniques. Currently, the repository includes the following projects:
https://github.com/kishanvyas308/ai-mini-projects

bfs-search dfs-search maze-solver minimax-algorithm python tic-tac-toe-ai tic-tac-toe-python

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This repository contains a collection of AI-based mini projects. Each project demonstrates the application of different AI algorithms and techniques. Currently, the repository includes the following projects:

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# AI Mini Projects

This repository contains a collection of AI-based mini projects. Each project demonstrates the application of different AI algorithms and techniques. Currently, the repository includes the following projects:

1. [Tic Tac Toe with AI](#tic-tac-toe-with-ai)
2. [Maze Search Algorithms](#maze-search-algorithms)

More projects will be added in the future.

## Tic Tac Toe with AI

This project is a GUI-based implementation of the classic Tic Tac Toe game, featuring an AI opponent that uses the minimax algorithm to make optimal moves.

### Features

- Play against an AI opponent
- User-friendly graphical interface using Tkinter
- Game board display
- Win condition checks
- Restart functionality

### Video - Demo

https://github.com/user-attachments/assets/483969d9-4111-4ebc-af76-70a42bc6b80e

### Files

- `src/tictactoe.py`: Main entry point of the game, handling the game loop and user input.
- `requirements.txt`: Lists the dependencies required for the project.

### Installation

1. Clone the repository:
```
git clone https://github.com/KishanVyas308/Ai-Mini-Projects.git
```
2. Navigate to the Tic Tac Toe project directory:
```
cd Ai-Mini-Projects/Tic-Tac-Toe-With-AI
```
3. Install the required dependencies:
```
pip install -r requirements.txt
```

### Usage

To start the game, run the following command:
```
python src/tictactoe.py
```

Enjoy playing Tic Tac Toe against a challenging AI!

## Maze Search Algorithms

This project demonstrates the implementation of various search algorithms to solve a maze. The maze is represented as a grid, and the algorithms find the path from the start point 'A' to the end point 'B'.

### Features

- Depth-First Search (DFS)
- Breadth-First Search (BFS)
- Visualization of the maze and the solution path

### Video - Demo

https://github.com/user-attachments/assets/33fba71b-7971-4de1-8b35-7a9940cdee72

### Files

- `maze.py`: Main script to run the maze solver.
- `maze1.txt`: Example maze file.

### Installation

1. Clone the repository:
```
git clone https://github.com/KishanVyas308/Ai-Mini-Projects.git
```
2. Navigate to the Maze Search Algorithms project directory:
```
cd Ai-Mini-Projects/Maze-Search-Algorithms
```

### Usage

To solve the maze, run the following command:
```
python maze.py maze1.txt
```

The solution will be printed in the console, and an image of the maze with the solution path will be saved as `maze.png`.

## Contributing

Contributions are welcome! Please fork this repository and submit a pull request with your changes. Ensure your code follows the project's coding standards and includes appropriate tests.

## License

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