most citedGlobally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes

3 citations · 3 across the 1 of their papers we have counts for

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cs.LG2021★ 3 cited

Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes

Guillermo Infante, Anders Jonsson, Vicenç Gómez

In this work we present a novel approach to hierarchical reinforcement learning for linearly-solvable Markov decision processes. Our approach assumes that the state space is partit…