Motor primitive discovery

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Nov 2012Publisher:IEEEJournal:2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL)

Authors: Philip S. Thomas; Andrew G. Barto;

doi: 10.1109/devlrn.2012.6400845

Motor primitive discovery

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Abstract

We present a method for autonomous on-line discovery of motor primitives for Markov decision processes with high-dimensional continuous action spaces. These biologically-inspired motor primitives require overhead to compute but form a compressed representation of the action set that allows for improved performance on subsequent learning tasks that have similar dynamics.

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University of Massachusetts Amherst
United States

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