Ronglong Cai

ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble

Offline reinforcement learning (RL) aims to learn from static datasets and thus faces the challenge of value estimation errors for out-of-distribution actions. The in-sample learning scheme addresses this issue by performing implicit TD backups that does not query the values of unseen actions. Howev…