MoET: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees

16 Jun 2019Marko VasicAndrija PetrovicKaiyuan WangMladen NikolicRishabh SinghSarfraz Khurshid

Deep Reinforcement Learning (DRL) has led to many recent breakthroughs on complex control tasks, such as defeating the best human player in the game of Go. However, decisions made by the DRL agent are not explainable, hindering its applicability in safety-critical settings... (read more)

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