Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
Published in International Conference on Machine Learning (ICML), 2023
This paper presents a novel safe reinforcement learning approach that can jointly learn the environment and optimize the control policy while effectively avoiding unsafe regions. The method introduces soft barriers to enforce hard safety constraints and incorporates safety probability optimization to ensure reliable performance in unknown stochastic environments.
Authors: Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
Citation
@inproceedings{wang2023enforcing, title={Enforcing hard constraints with soft barriers: Safe reinforcement learning in unknown stochastic environments}, author={Wang, Yixuan and Zhan, Simon Sinong and Jiao, Ruochen and Wang, Zhilu and Jin, Wanxin and Yang, Zhuoran and Wang, Zhaoran and Huang, Chao and Zhu, Qi}, booktitle={International Conference on Machine Learning}, pages={36593--36604}, year={2023}, organization={PMLR} }