Chia-Heng Hsu

From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning

Preference-based reinforcement learning (PbRL) avoids explicit reward engineering by learning from pairwise human preference feedback. Existing offline PbRL methods typically follow a two-stage pipeline, first learning a reward or preference model from labeled preferences and then performing offline…