Matin Moezzi

Data-Efficient Hierarchical Goal-Conditioned Reinforcement Learning Via Normalizing Flows

Hierarchical goal-conditioned reinforcement learning (H-GCRL) provides a powerful framework for tackling complex, long-horizon tasks by decomposing them into structured subgoals. However, its practical adoption is hindered by poor data efficiency and limited policy expressivity, especially in offlin…