Implementation of Breadth-First Exploration on Adaptive Grid for Reinforcement Learning (ICML 2024) in PyTorch. Our code is based on official implementation of DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning.
create conda environment
conda env create -n beag -f env.yaml python=3.7
conda activate beag
if permission denied,
chmod +x ./scripts/*.sh
To reproduce our experiments, please run the script provided below
./scripts/{ENV}.sh {GPU} {SEED}
example
./scripts/Reacher.sh 0 1
./scripts/AntMaze.sh 2 3
@inproceedings{yoon2024beag,
title={Breadth-First Exploration on Adaptive Grid for Reinforcement Learning},
author={Yoon, Youngsik and Lee, Gangbok and Ahn, Sungsoo and Ok, Jungseul},
booktitle={Forty-first International Conference on Machine Learning},
year={2024}
}