Tipping the Scales: Guidance and Intrinsically Motivated Behavior

Georg Martius, J. Michael Herrmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We propose a novel approach to learning in autonomous robots that relies on the dynamical maintenance of an actively sensitized sensorimotor loop. Very weak learning cues are sufficient to orient a robot towards the desired behavior which is then selected from the intrinsic exploratory movements rather than imposed by a control command. The learning paradigm is a form of guided self-organization and is comple-mentary to both active and intrinsically motivated learning. We present a systematic analysis of the learning algorithm in a robot control task and demonstrate its remarkable scalabil-ity with respect to the degrees of freedom of the system.
Original languageEnglish
Title of host publicationAdvances in Artificial Life, ECAL 2011
PublisherMIT Press
Number of pages8
ISBN (Electronic)978-0-262-29714-1
Publication statusPublished - 2011


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