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Dynamic organization of flocking behaviors in a large-scale boids model

Author

Listed:
  • Norihiro Maruyama

    (University of Tokyo)

  • Daichi Saito

    (University of Tokyo)

  • Yasuhiro Hashimoto

    (University of Tokyo)

  • Takashi Ikegami

    (University of Tokyo)

Abstract

A simulation of a half-million flock is studied using a simple boids model originally proposed by Craig Reynolds. It was modeled with a differential equation in 3D space with a periodic boundary. Flocking is collective behavior of active agents, which is often observed in the real world (e.g., starling swarms). It is, nevertheless, hard to rigorously define flocks (or their boundaries). First, even within the same swarm, the members are constantly updated, and second, flocks sometimes merge or divide dynamically. To define individual flocks and to capture their dynamic features, we applied a DBSCAN and a non-negative matrix factorization (NMF) to the boid dataset. Flocking behavior has different types of dynamics depending on the size of the flock. A function of different flocks is discussed with the result of NMF analysis.

Suggested Citation

  • Norihiro Maruyama & Daichi Saito & Yasuhiro Hashimoto & Takashi Ikegami, 2019. "Dynamic organization of flocking behaviors in a large-scale boids model," Journal of Computational Social Science, Springer, vol. 2(1), pages 77-84, January.
    • Handle: RePEc:spr:jcsosc:v:2:y:2019:i:1:d:10.1007_s42001-019-00037-9
    DOI: 10.1007/s42001-019-00037-9
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    References listed on IDEAS

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    1. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
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    Cited by:

    1. Tony Z. Jia & Yutetsu Kuruma, 2019. "Recent Advances in Origins of Life Research by Biophysicists in Japan," Challenges, MDPI, vol. 10(1), pages 1-21, April.

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