Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies

13 Mar 2018Tom ZahavyAvinatan HasidimHaim KaplanYishay Mansour

In this work, we provide theoretical guarantees for reward decomposition in deterministic MDPs. Reward decomposition is a special case of Hierarchical Reinforcement Learning, that allows one to learn many policies in parallel and combine them into a composite solution... (read more)

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