Contextual Policy Transfer in Reinforcement Learning Domains via Deep Mixtures-of-Experts

29 Feb 2020Michael GimelfarbScott SannerChi-Guhn Lee

In reinforcement learning, agents that consider the context, or current state, when selecting source policies for transfer have been shown to outperform context-free approaches. However, none of the existing approaches transfer knowledge contextually from model-based learners to a model-free learner... (read more)

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