Long Dinh Van The

Leveraging Mutual Information for Asymmetric Learning under Partial Observability

Even though partial observability is prevalent in robotics, most reinforcement learning studies avoid it due to the difficulty of learning a policy that can efficiently memorize past events and seek information. Fortunately, in many cases, learning can be done in an asymmetric setting where states a…