Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation

Chengqian Gao, Ke Xu, Liu Liu +3

A promising paradigm for offline reinforcement learning (RL) is to constrain the learned policy to stay close to the dataset behaviors, known as policy constraint offline RL. Howev…