This bit of code is a Python implementation of Nash genetic algorithm. It attempts to find Nash equilibrium using an evolutionary approach.
In game theory Nash's equilibrium is a state in which no player can do any better (say in terms of a utility function) by changing his action plan as long as other players stick to their plans. If a problem is relatively complex, analytic solutions may be hard and this is where pynashga comes in.
You need Python 3, the code is tested under Python 3.8. You should install numpy, matplotlib and scipy. Just download the code and see if you can run the game on the file multple_areas_comp1.py
We have submitted a paper which details the implementation. Should this get publish, we plan to update the README file.