Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

Nicholay Topin, Stephanie Milani, Fei Fang +1

Current work in explainable reinforcement learning generally produces policies in the form of a decision tree over the state space. Such policies can be used for formal safety veri…