13 citations · 46 across the 19 of their papers we have counts for
4 papers · 2 filters
GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models
Mianchu Wang, Rui Yang, Xi Chen +3
Offline Goal-Conditioned RL (GCRL) offers a feasible paradigm for learning general-purpose policies from diverse and multi-task offline datasets. Despite notable recent progress, t…
Corruption-Robust Offline Reinforcement Learning with General Function Approximation
Chenlu Ye, Rui Yang, Quanquan Gu +1
We investigate the problem of corruption robustness in offline reinforcement learning (RL) with general function approximation, where an adversary can corrupt each sample in the of…
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang, Han Zhong, Jiawei Xu +4
Offline reinforcement learning (RL) presents a promising approach for learning reinforced policies from offline datasets without the need for costly or unsafe interactions with the…
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?
Rui Yang, Yong Lin, Xiaoteng Ma +3
Offline goal-conditioned RL (GCRL) offers a way to train general-purpose agents from fully offline datasets. In addition to being conservative within the dataset, the generalizatio…