Jin-Ru Duan

Decoupling Policy Extraction for Offline Reinforcement Learning

This work revisits the conventional offline RL paradigm and proposes decoupling policy improvement from actor training, and trains the actor solely to model the behavior distribution and perform policy improvement at inference time by reranking multiple actor-generated proposals with a separately learned critic.