Offline Goal-Conditioned Reinforcement Learning for Safety-Critical Tasks with Recovery Policy
Chenyang Cao,Zichen Yan,Renhao Lu,Junbo Tan,Xueqian Wang,Chenyang Cao,Zichen Yan,Renhao Lu,Junbo Tan,Xueqian Wang
Offline goal-conditioned reinforcement learning (GCRL) aims at solving goal-reaching tasks with sparse rewards from an offline dataset. While prior work has demonstrated various approaches for agents to learn near-optimal policies, these methods encounter limitations when dealing with diverse constraints in complex environments, such as safety constraints. Some of these approaches prioritize goal ...
