Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning
Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi Jung-Su Ha Young-Jin Park Hyeok-Joo Chae Soon-Seo Park Han-Lim Choi
We present a hierarchical planning and control framework that enables an agent to perform various tasks and adapt to a new task flexibly. Rather than learning an individual policy for each particular task, the proposed framework, DISH, distills a hierarchical policy from a set of tasks by representation and reinforcement learning. The framework is based on the idea of latent variable models that r...