🐍 AI-Driven Snake Game

Welcome to the AI-Driven Snake Game! This project is a modern take on the classic Snake game, enhanced with artificial intelligence. Choose from various AI algorithms like A*, BFS, DFS, and Genetic Algorithm to see how they control the snake's movements toward its prey.

📜 Table of Contents

• 🐍 AI-Driven Snake Game
  • 📜 Table of Contents
  • 🌟 Overview
  • 🚀 Features
  • 🛠️ Installation
  • ▶️ Running the Game
  • 🕹️ Usage
  • ⚙️ Configuration
  • 🧠 AI Algorithms
  • 🤝 Contributing
  • 📜 License
  • 📬 Contact

🌟 Overview

This project leverages AI to control the snake in a grid-based environment. It provides a comparative analysis of different pathfinding and decision-making algorithms, visualizing their effectiveness in real-time.

🚀 Features

• Neural Network Control: Trained neural network to manage snake movements.
• Preset Algorithms: Implementations of A*, BFS, DFS, and Genetic Algorithm.
• Menu Interface: Graphical menu to select and switch between algorithms.
• Path Visualization: Real-time path highlighting to understand algorithm workings.
• Comparative Analysis: Compare different AI strategies in action.

🛠️ Installation

1. Clone the repository:

   git clone https://github.com/yourusername/snake-remake.git
   cd snake-remake

2. Install dependencies:

   pip install pygame

3. Set up the project: Run the setup script to configure the project environment.

   python setup.py

▶️ Running the Game

To start the game, run the main.py script:

python main.py

🕹️ Usage

1. Menu Navigation: Use the keyboard or mouse to navigate through the menu.
2. Select Algorithm: Choose an algorithm to control the snake.
3. Gameplay: Observe the snake's behavior and path as it approaches its prey.
4. Comparative Analysis: Switch between different algorithms to compare their performance.

⚙️ Configuration

Modify the configuration settings in src/config/Constants.py:

• Grid size and dimensions
• Initial snake speed and length
• Colors (snake color, prey color, background color)
• Key bindings

🧠 AI Algorithms

Preset Directory:

• A_STAR.py: Implementation of the A* pathfinding algorithm.
• BFS.py: Implementation of the Breadth-First Search algorithm.
• DFS.py: Implementation of the Depth-First Search algorithm.
• GA.py: Implementation of the Genetic Algorithm.

AI Directory:

• algorithm.py: General AI algorithms and utility functions.
• neural_network.py: Neural network implementations for AI-based control.

🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes. For major changes, please open an issue first to discuss what you would like to change.

📜 License

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

📬 Contact

For any questions or suggestions, feel free to reach out:

• Email: dresta.connect@gmail.com

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Feel free to reach out if you have any questions or need further assistance!