Exploration in Continuous Control Tasks via Continually Parameterized Skills

IEEE Transactions on Games, pp. 390-399, 2018.

Cited by: 1|Bibtex|Views18|DOI:https://doi.org/10.1109/TG.2018.2806007
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Abstract:

Applications of reinforcement learning to continuous control tasks often rely on a steady, informative reward signal. In videogames, however, tasks may be far easier to specify through a binary reward that indicates success or failure. In the absence of a steady, guiding reward, the agent may struggle to explore efficiently, especially if...More

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