Transferring Task Goals via Hierarchical Reinforcement Learning

Tech Report, 2018(2018)

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摘要
In this paper we demonstrate how hierarchical reinforcement learning architectures with guiding rewards can be used to separate high-level task understanding from low-level task execution and to exploit this separation of concerns for transferring high-level task goals eg across bodies with very different properties and capabilities.
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