Swarming in homogeneous environments: A social interaction based framework

被引:9
作者
Li, Xiaohai [1 ]
Xiao, Jizhong [1 ,2 ]
机构
[1] CUNY, Grad Ctr, Dept Elect Engn, New York, NY 10016 USA
[2] CUNY City Coll, New York, NY 10031 USA
基金
美国国家科学基金会;
关键词
Swarms; Collective motion; Self-organized group behavior; Nonsmooth analysis; Lyapunov stability analysis; FISH SCHOOLS; STABILITY ANALYSIS; MODEL; BEHAVIOR; INDIVIDUALS; ALIGNMENT; SYSTEM;
D O I
10.1016/j.jtbi.2010.02.016
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A great variety of biological groups form a self-organized swarming motion at some point during their life spans, which has two prominent collective features: common velocity and constant spacings among members. In this paper, we present a general individual-based motion framework to explain such collective motion of swarms in homogeneous environments. The motion framework utilizes the concept of social interactions that has been widely accepted throughout the literature. We assume that during the motion of the swarm, each member senses and interacts with its neighbors via virtual Attraction/Alignment/Repulsion (A/A/R) forces, while perceiving and following the gradient force of the environment. During the swarm's motion, the neighborhood and the interaction relations among members may dynamically change. To explicitly consider the effect of such dynamic change on the emergence of swarm's collective behavior, we use an algebraic graph to model the topology of the interaction and the neighborhood relations among the members. By using mathematical tools of nonsmooth analysis theory and Lyapunov stability theory, we analytically prove that if the A/A/R forces have limited ranges, and the attraction/repulsion forces are balanced at a certain range, the proposed framework leads to a parallel type of collective motion of the swarm. We mathematically show that the velocities of all swarm members asymptotically converge to a common value and the spacings among neighbors remain unchanging. In addition to the mathematical analysis, a few sets of simulation results are included to demonstrate the presented framework. The contributions of this paper are twofold: First, unlike most works in the literature that mainly use computer simulations to study the swarming phenomena, this paper provides an analytical methodology to investigate how the collective group behavior is self-organized by individual motions. Second, the presented motion framework works over a general range of A/A/R interactions. In other words, we analytically prove that the commonly used A/A/R model can lead to a collective motion of the swarm. In addition, we show that the alternative model in the literature that uses only attraction/repulsion (A/R) interactions is in fact a special case of the A/A/R model. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:747 / 759
页数:13
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