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Modulated Exploratory Dynamics Can Shape Self-Organized Behavior

Author

Listed:
  • FRANK HESSE

    (Max-Planck-Institute for Dynamics and Self-Organization, Bernstein Center for Computational Neuroscience Göttingen, Bunsenstrasse 10, 37073 Göttingen, Germany;
    Department for Nonlinear Dynamics, Georg-August-University Göttingen, Bunsenstrasse 10, 37073 Göttingen, Germany)

  • RALF DER

    (Max-Planck-Institute for Mathematics in the Sciences, Inselstrasse 22, 04103 Leipzig, Germany)

  • J. MICHAEL HERRMANN

    (University of Edinburgh, School of Informatics, 10 Crichton Street, Edinburgh, EH8 9AB, Scotland, UK)

Abstract

We study an adaptive controller that adjusts its internal parameters by self-organization of its interaction with the environment. We show that the parameter changes that occur in this low-level learning process can themselves provide a source of information to a higher-level context-sensitive learning mechanism. In this way, the context is interpreted in terms of the concurrent low-level learning mechanism. The dual learning architecture is studied in realistic simulations of a foraging robot and of a humanoid hand that manipulated an object. Both systems are driven by the same low-level scheme, but use the second-order information in different ways. While the low-level adaptation continues to follow a set of rigid learning rules, the second-order learning modulates the elementary behaviors and affects the distribution of the sensory inputs via the environment.

Suggested Citation

  • Frank Hesse & Ralf Der & J. Michael Herrmann, 2009. "Modulated Exploratory Dynamics Can Shape Self-Organized Behavior," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 273-291.
    • Handle: RePEc:wsi:acsxxx:v:12:y:2009:i:03:n:s0219525909002258
    DOI: 10.1142/S0219525909002258
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