A world of tiny creatures, driven by simple rules, yet creating complex societies.
Emergant is an ant colony simulator built with PyGame, where reinforcement learning drives the emergence of lifelike ant behaviors. Watch as virtual ants forage for food, defend their nests, and adapt their strategies over time—all without explicit scripting of their behaviors!
- 🌱 Reinforcement Learning – Ants from the same colony are all collected by one hivemind, and learn to bring food back to their colony using a system of rewards and penalties.
- 🧠 Neuroevolutionary Algorithm - The neural network structure of each hivemind evolves from generation to generation through natural selection.
- 🎮 PyGame Visualization – The simulation runs in real-time with an interactive graphical interface. There is also a neural network visualization utility to get deeper insights into the weights of the networks and to increase explainability.
(Insert GIFs or screenshots of the simulation in action!)
- Clone the repository:
git clone https://github.com/matanitah/emergant.git cd emergant - Install dependencies:
pip install -r requirements.txt
- Start the simulation:
python src/main.py
Reach out to me on Linkedin at https://www.linkedin.com/in/matan-itah/ if you are interested in becoming a collaborator.
MIT License – Free to use and modify!