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Embodied Artificial Intelligence pp 119–129Cite as

Self-Stabilization and Behavioral Diversity of Embodied Adaptive Locomotion

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3139))

Abstract

Locomotion is of fundamental importance in understanding adaptive behavior. In this paper we present two case studies of robot locomotion that demonstrate how higher level of behavioral diversity can be achieved while observing the principle of cheap design. More precisely, it is shown that, by exploiting the dynamics of the system-environment interaction, very simple controllers can be designed which is essential to achieve rapid locomotion. Special consideration must be given to the choice of body materials. We conclude with some speculation about the importance of locomotion for understanding cognition.

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Authors and Affiliations

  1. Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050, Zurich, Switzerland

    Fumiya Iida & Rolf Pfeifer

Authors
  1. Fumiya Iida
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  2. Rolf Pfeifer
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Editor information

Editors and Affiliations

  1. Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, CH-8050, Zurich, Switzerland

    Fumiya Iida  & Rolf Pfeifer  & 

  2. VUB AI Lab, Vrije Universiteit Brussels, Pleinlaan 2, 1050, Brussels, Belgium

    Luc Steels

  3. JST ERATO Asada Synergistic Intelligence Project,  

    Yasuo Kuniyoshi

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© 2004 Springer-Verlag Berlin Heidelberg

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Iida, F., Pfeifer, R. (2004). Self-Stabilization and Behavioral Diversity of Embodied Adaptive Locomotion. In: Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds) Embodied Artificial Intelligence. Lecture Notes in Computer Science(), vol 3139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27833-7_9

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  • DOI: https://doi.org/10.1007/978-3-540-27833-7_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22484-6

  • Online ISBN: 978-3-540-27833-7

  • eBook Packages: Springer Book Archive

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