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Code for our NeurIPS 2020 paper Improving Generalization in Reinforcement Learning with Mixture Regularization

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Improving Generalization in Reinforcement Learning with Mixture Regularization

[site] [paper]

This repo contains code for our NeurIPS 2020 paper Improving Generalization in Reinforcement Learning with Mixture Regularization. Code for PPO is based on train-procgen. Code for Rainbow is based on retro-baselines and anyrl-py.

🍜 Set up conda env and install OpenAI Baselines

conda env create --file py36_cu9_tf112.yml
conda activate py36_cu9_tf112

git clone https://github.com/openai/baselines.git
cd baselines
pip install -e .

🌭 Experiments & results

Check out experiments README for running different experiments. You may also use the scripts in experiments folder to start training. All results are available at Google Drive.

Citation

@misc{wang2020improving,
      title={Improving Generalization in Reinforcement Learning with Mixture Regularization}, 
      author={Kaixin Wang and Bingyi Kang and Jie Shao and Jiashi Feng},
      year={2020},
      eprint={2010.10814},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

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Code for our NeurIPS 2020 paper Improving Generalization in Reinforcement Learning with Mixture Regularization

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