Official Implementation of the Paper "GAN-based Intrinsic Exploration For Sample Efficient Reinforcement Learning" ( https://arxiv.org/abs/2206.14256 )
Most of the A2C codes is taken from the repository ttps://github.com/jcwleo/mario_rl and then updated according to this work.
If you'd like to cite this repository or the paper, you can use the following bibtex:
@conference{icaart22,
author={Doğay Kamar. and Nazím Üre. and Gözde Ünal.},
title={GAN-based Intrinsic Exploration for Sample Efficient Reinforcement Learning},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2022},
pages={264-272},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010825500003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}python3 main_mario.pyor
python3 main_montezuma.py