Snake Game with Reinforcement Learning

Description

Snake Game with Reinforcement Learning is a project that combines classic game development with artificial intelligence. The Snake game is implemented using the Pygame library, and an AI agent is trained to play the game using the Q-learning algorithm powered by PyTorch. The goal is to showcase the implementation of a reinforcement learning algorithm in a gaming environment.

Features

• Snake Game: Classic Snake game implemented using Pygame.
• Reinforcement Learning: Q-learning algorithm applied for training an AI agent.
• PyTorch Integration: Utilizing PyTorch for neural network implementation.
• Flexible and Extendable: Easily extendable for experimenting with different algorithms or game modifications.

Installation

1. Clone the repository:

   git clone https://github.com/iarslankhalid/RL_snake_game.git
   cd RL_snake_game
   pip install -r requirements.txt
   

Usage

1. Setup: Complete all the Installation process
2. Run agent.py file
3. You can use the pre-trained parameters by setting LOAD_PREVIOUS_MODEL = True in model.py
4. Or you can train the snake from start.
5. Explore & Experiment:
   • Tweak parameters and configurations in model.py for customization.
   • Extend the project by implementing additional features or experimenting with different reinforcement learning algorithms.

Licence

This project is licence under MIT Licence

Contact

• Email: [email protected]
• LinkedIn: https://www.linkedin.com/in/iarslankhalid/