Hierarchical Reinforcement Learning for Deep Goal Reasoning: An Expressiveness Analysis

21 Jun 2020Weihang YuanHéctor Muñoz-Avila

Hierarchical DQN (h-DQN) is a two-level architecture of feedforward neural networks where the meta level selects goals and the lower level takes actions to achieve the goals. We show tasks that cannot be solved by h-DQN, exemplifying the limitation of this type of hierarchical framework (HF)... (read more)

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