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Adaptive Coupling and Intersubjectivity in Simulated Turn-Taking Behaviour

  • Hiroyuki Iizuka
  • Takashi Ikegami
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2801)

Abstract

Turn-taking behaviour is simulated with a coupled agents system. Each agent is modelled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outputs and to hold the internal dynamics. Agents are developed to take turns on a two dimensional arena by causing the network structures to evolve.

Turn-taking is established using either regular or chaotic behaviour of the agents. It is found that chaotic turn-takers are more sensitive to the adaptive inputs from the other agent. On the other hand, regular turn-takers are comparatively insensitive to noisy inputs due to their restricted dynamics. From various observations, including turn-taking with virtual agents, we claim that the chaotic turn-taking agents become less robust when coping with virtual agents but at the same time, those agents are more adaptable to each other than the regular turn-taking agents. All these findings are discussed and compared with Trevarthen’s double monitor experiments.

Keywords

Mobile Robot Recurrent Neural Network Joint Attention Virtual Agent Adaptive 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 2003

Authors and Affiliations

  • Hiroyuki Iizuka
    • 1
  • Takashi Ikegami
    • 1
  1. 1.Department of General Systems Sciences, The Graduate School of Arts and SciencesUniversity of TokyoTokyoJapan

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