cGOAI is a Python project that combines Conway's Game of Life with machine learning. It generates life forms in the Game of Life using a trained neural network model. This project provides a continuous simulation of evolving patterns in the Game of Life.
Conway's Game of Life is a cellular automaton devised by mathematician John Conway. It consists of a grid of cells that evolve over generations based on simple rules. In this project, we use a neural network to generate initial configurations for the Game of Life, allowing for the creation of diverse life forms.
- Clone the repository:
git clone https://github.com/dvsloth/cGOAI.git cd cGOAI
- Install the required dependencies:
CD into the requirements folder pip install -r requirements.txt
Train the machine learning model:
- Inside the "train" folder
py train-proper.py
Run the Game of Life simulation:
- Execute the script in the main folder
py gol.py
In the train-proper.py
file, you can customize the sampling size, grid size and epochs.
Grid Size **MUST** match the Grid size in `gol.py`, else it will error out
In the gol.py
you can customize the Grid Size (see above for disclaimer lol)
This project is licensed under the MIT License. Please see the LICENSE file located in the "etc" folder for details.