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Virtual Partner Interaction (VPI): Exploring Novel Behaviors via Coordination Dynamics

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  • J A Scott Kelso
  • Gonzalo C de Guzman
  • Colin Reveley
  • Emmanuelle Tognoli

Abstract

Inspired by the dynamic clamp of cellular neuroscience, this paper introduces VPI—Virtual Partner Interaction—a coupled dynamical system for studying real time interaction between a human and a machine. In this proof of concept study, human subjects coordinate hand movements with a virtual partner, an avatar of a hand whose movements are driven by a computerized version of the Haken-Kelso-Bunz (HKB) equations that have been shown to govern basic forms of human coordination. As a surrogate system for human social coordination, VPI allows one to examine regions of the parameter space not typically explored during live interactions. A number of novel behaviors never previously observed are uncovered and accounted for. Having its basis in an empirically derived theory of human coordination, VPI offers a principled approach to human-machine interaction and opens up new ways to understand how humans interact with human-like machines including identification of underlying neural mechanisms.

Suggested Citation

  • J A Scott Kelso & Gonzalo C de Guzman & Colin Reveley & Emmanuelle Tognoli, 2009. "Virtual Partner Interaction (VPI): Exploring Novel Behaviors via Coordination Dynamics," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-11, June.
    • Handle: RePEc:plo:pone00:0005749
    DOI: 10.1371/journal.pone.0005749
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    References listed on IDEAS

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    1. Sören Krach & Frank Hegel & Britta Wrede & Gerhard Sagerer & Ferdinand Binkofski & Tilo Kircher, 2008. "Can Machines Think? Interaction and Perspective Taking with Robots Investigated via fMRI," PLOS ONE, Public Library of Science, vol. 3(7), pages 1-11, July.
    2. Raoul Huys & Breanna E Studenka & Nicole L Rheaume & Howard N Zelaznik & Viktor K Jirsa, 2008. "Distinct Timing Mechanisms Produce Discrete and Continuous Movements," PLOS Computational Biology, Public Library of Science, vol. 4(4), pages 1-8, April.
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    1. Iran R Roman & Auriel Washburn & Edward W Large & Chris Chafe & Takako Fujioka, 2019. "Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: A dynamical systems approach," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-32, October.
    2. Chao Zhai & Francesco Alderisio & Piotr Słowiński & Krasimira Tsaneva-Atanasova & Mario di Bernardo, 2016. "Design of a Virtual Player for Joint Improvisation with Humans in the Mirror Game," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-17, April.
    3. Auriel Washburn & Rachel W Kallen & Maurice Lamb & Nigel Stepp & Kevin Shockley & Michael J Richardson, 2019. "Feedback delays can enhance anticipatory synchronization in human-machine interaction," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-17, August.
    4. Viviane Kostrubiec & Guillaume Dumas & Pier-Giorgio Zanone & J A Scott Kelso, 2015. "The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-24, November.
    5. Gregory Zelic & Denis Mottet & Julien Lagarde, 2012. "Behavioral Impact of Unisensory and Multisensory Audio-Tactile Events: Pros and Cons for Interlimb Coordination in Juggling," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.

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