This is the implementation of Stackelberg Decision Transformer (STEER) for our paper accepted by ICML2024: Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach.
pip install -r requirements.txt
Following the instructios in https://github.com/openai/mujoco-py and https://github.com/schroederdewitt/multiagent_mujoco to setup a mujoco environment. In the end, remember to set the following environment variables:
LD_LIBRARY_PATH=${HOME}/.mujoco/mujoco200/bin;
LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libGLEW.so
Please following the instructios in https://github.com/google-research/football.
When your environment is ready, you could run shells in the "scripts" folder with algo="steer". For example:
./train_matrix.sh
./train_football.sh
./train_mujoco.shIf you would like to change the configs of experiments, you could modify sh files or look for config.py for more details.
@InProceedings{pmlr-v235-zhang24au,
title = {Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach},
author = {Zhang, Bin and Mao, Hangyu and Li, Lijuan and Xu, Zhiwei and Li, Dapeng and Zhao, Rui and Fan, Guoliang},
booktitle = {Proceedings of the 41st International Conference on Machine Learning},
pages = {59559--59575},
year = {2024},
editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix},
volume = {235},
series = {Proceedings of Machine Learning Research},
month = {21--27 Jul},
publisher = {PMLR},
pdf = {https://raw.githubusercontent.com/mlresearch/v235/main/assets/zhang24au/zhang24au.pdf},
url = {https://proceedings.mlr.press/v235/zhang24au.html},
}