📝 Publications
Reinforcement Learning
NeurIPS 2025
Robust Policy Expansion for Offline-to-Online RL
under Diverse Data Corruption
Longxiang He, Deheng Ye, Junbo Tan, Xueqian Wang, Li Shen
- We propose RPEX, an Offline-to-Online method that improves the performance of offline pre- trained RL policies under a wide range of data corruptions.
AlignIQL: Policy Alignment in Implicit Q-Learning through Constrained Optimization , Arxiv 2024, Longxiang He, Li Shen, Junbo Tan, Xueqian Wang
- TLDR: We introduce a new method (AlignIQL) to extract the policy from the IQL-style value function and explain when IQL can utilize weighted regression for policy extraction.
DiffCPS: Diffusion Model based Constrained Policy Search for Offline Reinforcement Learning, Arxiv 2024, Longxiang He, Li Shen, Linrui Zhang, Junbo Tan, Xueqian Wang
- TLDR: DiffCPS integrates diffusion-based policies into Advantage-Weighted Regression (AWR) via a primal-dual framework and offers insights into the advantages of employing diffusion models in offline decision-making, as well as elucidates the relationship between AWR and TD3+BC.
FOSP: Fine-tuning Offline Safe Policy through World Models, ICLR 2025, Chenyang Cao, Yucheng Xin, Silang Wu, Longxiang He, Zichen Yan, Junbo Tan, Xueqian Wang