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Emergence of Interaction among Adaptive Agents

  • Georg Martius
  • Stefano Nolfi
  • J. Michael Herrmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5040)

Abstract

Robotic agents can self-organize their interaction with the environment by an adaptive “homeokinetic” controller that simultaneously maximizes sensitivity of the behavior and predictability of sensory inputs. Based on previous work with single robots, we study the interaction of two homeokinetic agents. We show that this paradigm also produces quasi-social interactions among artificial agents. The results suggest that homeokinetic learning generates social behavior only in the the context of an actual encounter of the interaction partner while this does not happen for an identical stimulus pattern that is only replayed. This is in agreement with earlier experiments with human subjects.

Keywords

Autonomous Robot Social Contingency Agency Detection Evolutionary Robotic Robotic Agent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Georg Martius
    • 1
    • 2
    • 3
  • Stefano Nolfi
    • 4
  • J. Michael Herrmann
    • 1
    • 2
    • 5
  1. 1.Bernstein Center for Computational Neuroscience GöttingenGöttingenGermany
  2. 2.Institute for Nonlinear DynamicsUniversity of GöttingenGöttingenGermany
  3. 3.Max Planck Institute for Dynamics and Self-OrganizationGöttingenGermany
  4. 4.Institute of Cognitive Sciences and TechnologiesLARRALRomaItaly
  5. 5.School of Informatics, Institute for Perception, Action and BehaviorEdinburgh UniversityEdinburghScotland U.K.

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