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Explaining a Reinforcement Learning Agent via Prototyping

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soroush-bn/ProtoX

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To run the code, you should 
1) create python 3.7 virtual environment
2) pip install -r requirements.txt
3) obtain trained agents: https://github.com/DLR-RM/rl-trained-agents and https://github.com/uvipen/Super-mario-bros-PPO-pytorch
4) obtain atari ROMS: https://github.com/openai/atari-py
5) ProtoX, ResNet-BC, and VIPER have associated jupyter notebooks; GAIfO is to be run on the command line

To run ProtoX or ResNet-BC on mario games, use files in ProtoX_Mario folder
To run ProtoX or ResNet-BC on atari games, use files in ProtoX_Atari folder

VIPER and GAIFO files are in the baselines folder

Training data and model checkpoints were not included as they would exceed the 100MB limit

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