Coarse Collective Dynamics of Animal Groups

  • Thomas A. Frewen
  • Iain D. Couzin
  • Allison Kolpas
  • Jeff Moehlis
  • Ronald Coifman
  • Ioannis G. Kevrekidis
Conference paper

DOI: 10.1007/978-3-642-14941-2_16

Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 75)
Cite this paper as:
Frewen T.A., Couzin I.D., Kolpas A., Moehlis J., Coifman R., Kevrekidis I.G. (2011) Coarse Collective Dynamics of Animal Groups. In: Gorban A., Roose D. (eds) Coping with Complexity: Model Reduction and Data Analysis. Lecture Notes in Computational Science and Engineering, vol 75. Springer, Berlin, Heidelberg

Abstract

The coarse-grained, computer-assisted analysis of models of collective dynamics in animal groups involves (a) identifying appropriate observables that best describe the state of these complex systems and (b) characterizing the dynamics of such observables. We devise “equation-free” simulation protocols for the analysis of a prototypical individual-based model of collective group dynamics. Our approach allows the extraction of information at the macroscopic level via parsimonious usage of the detailed, “microscopic” computational model. Identification of meaningful coarse observables (“reduction coordinates”) is critical to the success of such an approach, and we use a recently-developed dimensionality-reduction approach (diffusion maps) to detect good observables based on data generated by local model simulation bursts. This approach can be more generally applicable to the study of coherent behavior in a broad class of collective systems (e.g., collective cell migration).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Thomas A. Frewen
    • 1
  • Iain D. Couzin
    • 3
  • Allison Kolpas
    • 4
  • Jeff Moehlis
    • 5
  • Ronald Coifman
    • 6
  • Ioannis G. Kevrekidis
    • 1
    • 2
  1. 1.Department of Chemical EngineeringPrinceton UniversityPrincetonUSA
  2. 2.PACM and MathematicsPrinceton UniversityPrincetonUSA
  3. 3.Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonUSA
  4. 4.Department of Mathematical SciencesUniversity of DelawareNewarkUSA
  5. 5.Department of Mechanical EngineeringUniversity of CaliforniaSanta BarbaraUSA
  6. 6.Department of MathematicsYale UniversityNew HavenUSA

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