Consistency Policy Q-Learning (CPQL)
November 11, 2025 ยท View on GitHub
This is the official PyTorch implementation of the paper "Boosting Continuous Control with Consistency Policy". For those interested in delving deeper into our research, you can find detailed versions of our paper:
For an extended read, including the appendix, check out the Arxiv Version. For the conference-specific details as presented at AAMAS 2024, access the AAMAS 2024 Version.
๐ ๏ธ Installation Instructions
Clone this repository.
git clone https://github.com/cccedric/cpql.git
cd cpql
Create a virtual environment.
conda env create -f cpql_env.yaml
Install extra dependencies.
- Install mujoco210 and mujoco-py following instructions here.
- Install D4RL following instructions here.
๐ป Reproducing Experimental Results
Training for offline tasks
python main.py --rl_type offline --env_name hopper-medium-expert-v2
Training for online tasks
python main.py --rl_type online --env_name Hopper-v3
โ๏ธ Contact
For any questions, please feel free to email chenyuhui2022@ia.ac.cn.
๐ Acknowledgement
Our code is built upon consistency models, Diffusion-QL. We thank all these authors for their nicely open sourced code and their great contributions to the community.
๐ท๏ธ License
This repository is released under the GNU license. See LICENSE for additional details.
๐ Citation
If you find our research helpful and would like to reference it in your work, please consider using one of the following citations, depending on the format that best suits your needs:
For the Arxiv version:
@article{chen2023boosting,
title={Boosting Continuous Control with Consistency Policy},
author={Chen, Yuhui and Li, Haoran and Zhao, Dongbin},
journal={arXiv preprint arXiv:2310.06343},
year={2023}
}
Or, for citing our work presented at the conference of AAMAS 2024:
@inproceedings{chen2023boosting,
author={Yuhui Chen and Haoran Li and Dongbin Zhao},
title={Boosting Continuous Control with Consistency Policy},
booktitle={Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, {AAMAS} 2024, Auckland, New Zealand, May 6-10, 2024},
pages={335--344},
publisher={ACM},
doi={10.5555/3635637.3662882},
}