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The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

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Published on: January 19, 2019

A continuum three-zone model for swarms.

Jennifer M Miller1, Allison Kolpas, Joao Plinio Juchem Neto

  • 1Department of Mathematical Sciences, University of Delaware, Newark, DE 19716, USA.

Bulletin of Mathematical Biology
|July 30, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces three continuum models to explain swarm behavior, revealing that attraction strength relative to repulsion and orientation dictates swarm stability and structure.

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Area of Science:

  • Mathematical Biology
  • Complex Systems
  • Collective Behavior

Background:

  • Swarm behavior in biological aggregations is complex.
  • Understanding emergent structures from individual interactions is key.
  • Continuum models offer a macroscopic view of collective dynamics.

Purpose of the Study:

  • To develop and analyze continuum models for swarm behavior.
  • To explain coherent structures observed in biological aggregations.
  • To link individual-based interactions to macroscopic swarm dynamics.

Main Methods:

  • Developed three distinct three-zone, continuum models (first-order variable-speed, second-order variable-speed, second-order constant-speed).
  • Employed convolution-based modeling for repulsion, orientation, and attraction zones.
  • Utilized linear stability analysis to study perturbations in uniform swarms.
  • Validated models by comparing with individual-based simulations.

Main Results:

  • Swarm stability depends on the balance between attraction, repulsion, and orientation strengths.
  • Unstable regimes can lead to radially symmetric attractors with variable density.
  • Other unstable regimes result in incoherent swarming states.
  • Continuum models accurately predict swarm behavior observed in individual-based models.

Conclusions:

  • The developed continuum models provide a framework for understanding swarm dynamics.
  • The relative strengths of social interactions are critical determinants of swarm structure.
  • These models can predict the emergence of both ordered and disordered collective behaviors.