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2007
Springer

Reducing Trials by Thinning-Out in Skill Discovery

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Reducing Trials by Thinning-Out in Skill Discovery
In this paper, we propose a new concept, thinning-out, for reducing the number of trials in skill discovery. Thinning-out means to skip over such trials that are unlikely to improve discovering results, in the same way as “pruning” in a search tree. We show that our thinningout technique significantly reduces the number of trials. In addition, we apply thinning-out to the discovery of good physical motions by legged robots in a simulation environment. By using thinning-out, our virtual robots can discover sophisticated motions that is much different from the initial motion in a reasonable amount of trials.
Hayato Kobayashi, Kohei Hatano, Akira Ishino, Ayum
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2007
Where DIS
Authors Hayato Kobayashi, Kohei Hatano, Akira Ishino, Ayumi Shinohara
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