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Feedback delays can enhance anticipatory synchronization in human-machine interaction

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  • Auriel Washburn
  • Rachel W Kallen
  • Maurice Lamb
  • Nigel Stepp
  • Kevin Shockley
  • Michael J Richardson

Abstract

Research investigating the dynamics of coupled physical systems has demonstrated that small feedback delays can allow a dynamic response system to anticipate chaotic behavior. This counterintuitive phenomenon, termed anticipatory synchronization, has been observed in coupled electrical circuits, laser semi-conductors, and artificial neurons. Recent research indicates that the same process might also support the ability of humans to anticipate the occurrence of chaotic behavior in other individuals. Motivated by this latter work, the current study examined whether the process of feedback delay induced anticipatory synchronization could be employed to develop an interactive artificial agent capable of anticipating chaotic human movement. Results revealed that incorporating such delays within the movement-control dynamics of an artificial agent not only enhances an artificial agent’s ability to anticipate chaotic human behavior, but to synchronize with such behavior in a manner similar to natural human-human anticipatory synchronization. The implication of these findings for the development of human-machine interaction systems is discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:plo:pone00:0221275
    DOI: 10.1371/journal.pone.0221275
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    References listed on IDEAS

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    1. 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.
    2. Toral, Raúl & Masoller, C & Mirasso, Claudio R & Ciszak, M & Calvo, O, 2003. "Characterization of the anticipated synchronization regime in the coupled FitzHugh–Nagumo model for neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 325(1), pages 192-198.
    3. 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.
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    Cited by:

    1. Kelty-Stephen, Damian G. & Mangalam, Madhur, 2024. "Additivity suppresses multifractal nonlinearity due to multiplicative cascade dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).

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