Hierarchy through Composition with Linearly Solvable Markov Decision Processes

8 Dec 2016Andrew M. SaxeAdam EarleBenjamin Rosman

Hierarchical architectures are critical to the scalability of reinforcement learning methods. Current hierarchical frameworks execute actions serially, with macro-actions comprising sequences of primitive actions... (read more)

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