Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning

Tongzhou Mu, Kaixiang Lin, Feiyang Niu +1

We present a two-step hybrid reinforcement learning (RL) policy that is designed to generate interpretable and robust hierarchical policies on the RL problem with graph-based input…