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Behavior spread transitions from simple to complex contagion in collective decision-making, even without thresholds. The pace of behavior and network structure critically influence transmission dynamics in animals, humans, and robots.

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Area of Science:

  • Collective behavior
  • Social network dynamics
  • Robotics

Background:

  • Behavior propagation in social networks can shift from simple contagion (pairwise interactions) to complex contagion (social influence/reinforcement).
  • Previous observations of this transition were limited to threshold-based decision-making with binary choices.

Purpose of the Study:

  • To investigate if the simple-to-complex contagion transition occurs in non-threshold-based decision-making models.
  • To explore the factors influencing this transition in archetypal distributed decision-making systems.

Main Methods:

  • Theoretical modeling of behavior spread in distributed decision-making.
  • Experimental validation using a multi-robot system.

Main Results:

  • Demonstrated a transition from simple to complex contagion in a model without thresholds or nonlinearities.
  • Identified the intrinsic pace of spreading behavior as a key determinant of contagion type.
  • Showed that network topology significantly impacts behavioral transmission effectiveness, similar to threshold-based models.

Conclusions:

  • The simple-to-complex contagion transition is not exclusive to threshold-based systems.
  • Behavioral pace and network topology are crucial factors in understanding behavioral spread in collective decision-making.
  • Findings provide new avenues for studying behavioral contagions and designing cooperative robotic systems.