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Self-organized sorting limits behavioral variability in swarms.

Katherine Copenhagen1, David A Quint2,3, Ajay Gopinathan1

  • 1University of California Merced, Merced CA, USA.

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|August 24, 2016
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Summary
This summary is machine-generated.

Swarms with behavioral variability can self-organize, sorting out non-aligning individuals to maintain collective motion. This robust mechanism allows mixed populations to regulate composition and persist in swarming states.

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Area of Science:

  • Collective behavior
  • Agent-based modeling
  • Self-organization

Background:

  • Swarming involves collective motion from local interactions in identical individuals.
  • Understanding how behavioral variability affects swarming is crucial for complex systems.

Purpose of the Study:

  • Investigate the impact of behavioral variability on finite swarms.
  • Determine the critical fraction of non-aligners that disrupt swarming.
  • Explore mechanisms for maintaining swarming in heterogeneous populations.

Main Methods:

  • Agent-based simulations of swarms with alignment and cohesive interactions.
  • Analysis of swarm dynamics under varying fractions of non-aligning agents.
  • Modeling of evolutionary dynamics coupled with self-organized sorting.

Main Results:

  • Swarming is abolished above a critical fraction of non-aligners.
  • Swarms can dynamically reorganize and sort excess non-aligners.
  • This sorting mechanism persists in populations with distributed alignment interactions.
  • Self-organized sorting influences evolutionary dynamics, leading to stable equilibrium populations.

Conclusions:

  • Behavioral variability in swarms can be robustly managed through self-organized sorting.
  • Heterogeneous populations can maintain collective swarming states via composition regulation.
  • This mechanism offers insights into the evolution of social behaviors and population dynamics.