Haeun Kim

Dynamics-Aware Planning Representation for Zero-Shot Reinforcement Learning (Student Abstract)

Offline Zero-Shot Reinforcement Learning requires an agent to solve unseen tasks using only a fixed offline dataset without explicit rewards. A central challenge is learning representations that capture both high-level long-term planning and low-level physical dynamics. We propose a novel framework,