Theory in Biosciences

, Volume 131, Issue 3, pp 129–137 | Cite as

Variants of guided self-organization for robot control

Original Paper

Abstract

Autonomous robots can generate exploratory behavior by self-organization of the sensorimotor loop. We show that the behavioral manifold that is covered in this way can be modified in a goal-dependent way without reducing the self-induced activity of the robot. We present three strategies for guided self-organization, namely by using external rewards, a problem-specific error function, or assumptions about the symmetries of the desired behavior. The strategies are analyzed for two different robots in a physically realistic simulation.

Keywords

Guided self-organization Autonomous robots Homeokinesis Machine learning 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  1. 1.Bernstein Center for Computational Neuroscience and Max Planck Institute for Dynamics and Self-OrganizationGöttingenGermany
  2. 2.Institute for Perception, Action and BehaviourSchool of Informatics, University of EdinburghEdinburghUK

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