Utilizing Skipped Frames in Action Repeats for Improving Sample Efficiency in Reinforcement Learning
This repository implements the paper "Utilizing Skipped Frames in Action Repeats for Improving Sample Efficiency in Reinforcement Learning".
All of the dependencies are in the conda_env.yml file. They can be installed manually or with the following command:
conda env create -f conda_env.yml
Quick start: bash scripts/cartpole/run.sh
This code is implemented on top of SAC Pytorch.
This work was supported in part by the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2021-0-01381, Development of Causal AI through Video Understanding) and in part by the Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2022-0-00951, Development of Uncertainty-Aware Agents Learning by Asking Questions).
@ARTICLE{9793636,
author={Luu, Tung M. and Nguyen, Thanh and Vu, Thang and Yoo, Chang D.},
journal={IEEE Access},
title={Utilizing Skipped Frames in Action Repeats for Improving Sample Efficiency in Reinforcement Learning},
year={2022},
volume={10},
number={},
pages={64965-64975},
doi={10.1109/ACCESS.2022.3182107}
}