In this project, we combine the concepts of neural networks and genetic algorithms. Utilizing Python's NeuroEvolution of Augmenting Topologies (NEAT) package, we generate and evolve simple neural networks. These networks are trained to map inputs to outputs, enabling us to analyze and better understand how the system learns and adapts. This method offers a unique approach to machine learning and artificial intelligence.

Ensure you have Python (3.6 or newer) installed on your system. You can then install the required packages using pip:

pip install neat-python
pip install matplotlib

Simply run the main script neural_evolution.py to start the evolution and training process. The script will print out information about the ongoing evolution process.

Once the training is complete, the script will use matplotlib to visualize the best neural network from the population.

python neural_evolution.py

Contributions are welcome! Please feel free to submit a Pull Request.

This project is licensed under the terms of the MIT license.