Morphologies of self-organizing swarms in 3D swarm chemistry

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

A three-dimensional version of the Swarm Chemistry model is presented. Self-organization and morphogenesis of heterogeneous swarms in the 3D model were compared to those in the original 2D version. It was observed that the resulting patterns generally had remarkable robustness against dimensionality change, while some swarms were susceptible to the change. Further experiments showed that it was often sufficient to make minimal parameter adjustments in order to recover the original topological and dynamical properties of those susceptible swarms in 3D, although the dependence on parameters varied case by case with no generic parameter mapping between 2D and 3D.

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation
Pages577-584
Number of pages8
DOIs
Publication statusPublished - 2012 Aug 13
Externally publishedYes
Event14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
Duration: 2012 Jul 72012 Jul 11

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation

Other

Other14th International Conference on Genetic and Evolutionary Computation, GECCO'12
CountryUnited States
CityPhiladelphia, PA
Period12/7/712/7/11

Keywords

  • 3D
  • artificial chemistry
  • artificial life
  • morphology
  • spatial dimension
  • swarm chemistry
  • swarms

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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  • Cite this

    Sayama, H. (2012). Morphologies of self-organizing swarms in 3D swarm chemistry. In GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation (pp. 577-584). (GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation). https://doi.org/10.1145/2330163.2330245