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Evoman is a video game playing framework to be used as a testbed for optimization algorithms.

A demo can be found here: https://www.youtube.com/watch?v=ZqaMjd1E4ZI

To install requirements type in command: pip install -r requirements.txt

If you want to train NN with DEAP network run: python controller_specialist_deap.py

or

python controller_generalist_deap.py

In the file config.yaml there's a set of parameters you can tune. The config utilizes hydra library.

When you trained neural net from the above script you can see it in action with the following command: python controller_specialist_deap.py

All files ending with "deap"

All files in the folder "neat"

In order to run training with automatic hyperparameter search, you can run one of the following commands:

python controller_specialist_deap.py --multirun

or

python controller_generalist_deap.py --multirun

The results of your experiments can be found in directory multirun/{timestamp}/optimization_results.yaml

"optimization_" files are used to find the best solution

"contoller_..." these files run the soulution found by "optimization_..." files

(for Task 1 consider just the files containing "specialist" in their name

The given neural network is in the file "demo_controller.py"

All files containing "dummy" are draft files from where we can start to implement our own solutions

The neural net that was implemented by Jacob is in the folder "evolve"