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

Norihiro Maruyama (), Daichi Saito (), Yasuhiro Hashimoto () and Takashi Ikegami ()
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Norihiro Maruyama: University of Tokyo
Daichi Saito: University of Tokyo
Yasuhiro Hashimoto: University of Tokyo
Takashi Ikegami: University of Tokyo

Journal of Computational Social Science, 2019, vol. 2, issue 1, No 9, 77-84

Abstract: 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.

Keywords: Flocking; Boids; NMF; Parallel computing (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s42001-019-00037-9

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