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Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining
George Konidaris · Andrew G Barto
We introduce skill chaining, a skill discovery method for reinforcement learning agents in continuous domains, that builds chains of skills leading to an end-of-task reward. We demonstrate experimentally that it creates skills that result in performance benefits in a challenging continuous domain.
Author Information
George Konidaris (Brown University)
Andrew G Barto (University of Massachusetts)
Related Events (a corresponding poster, oral, or spotlight)
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2009 Poster: Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining »
Thu. Dec 10th 03:00 -- 07:59 AM Room
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