https://github.com/algoboy-kevin/neat-snake

Using evolutionary algorithm to solve Snake game
https://github.com/algoboy-kevin/neat-snake

artificial-intelligence neat pygame python reinforcement-learning snake-game

Last synced: 3 months ago
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Using evolutionary algorithm to solve Snake game

• Host: GitHub
• URL: https://github.com/algoboy-kevin/neat-snake
• Owner: algoboy-kevin
• Created: 2024-07-28T07:05:59.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-07-31T14:09:57.000Z (11 months ago)
• Last Synced: 2025-01-30T22:15:52.345Z (5 months ago)
• Topics: artificial-intelligence, neat, pygame, python, reinforcement-learning, snake-game
• Language: Python
• Homepage:
• Size: 10 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# neat-snake

This Python repository contains a testing environment and implementation of the NEAT algorithm for the classic game of Snake.

![alt text](https://assets.algoboy-kevin.com/snake-neat.png)

The Snake game is played on a 10x10 map. Each time the snake eats an apple, its length increases and the fitness score is incremented by 1. The goal is to achieve a fitness score of 20.

## Installation

To install the required dependencies, run the following command`pip install -r requirements.txt`

## Usage

There are several options available for running the Snake game:

1. **Test Environment**: To test the environment, execute the following command: `python main.py test`

2. **Train Snake**: To train the snake using the NEAT algorithm, use the following command: `python main.py train`

3. **Save and Create Winner Model**: To save and create a winner model after training, run the following command: `python main.py save`

4. **Run Trained Model**: To run a trained model, execute the following command: `python main.py run`

5. **Run Master Model**: To run the master model, execute the following command: `python main.py run_master`

Note: The last two commands are the same, but provided separately for clarity.

## Contributors

- [Daniel Chang](https://github.com/danielchang2002) - Snake env logic and network render reference. 

Feel free to contribute to this project by submitting pull requests or suggesting improvements. Happy coding!