具有拓扑相互作用和瞬态领导的蜂群动力学动力学描述

Giacomo Albi, Federica Ferrarese
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摘要

多尺度建模与仿真》,第 22 卷第 3 期,第 1169-1195 页,2024 年 9 月。 摘要本文提出了一个描述鸟类集体运动的模型。该模型引入了自发的方向变化,这些变化由少数几个代理(在此称为领导者)初始化,其影响作用于它们的近邻(在下文中称为跟随者)。我们从微观层面入手,建立了一个动力学模型,描述了具有瞬时领导能力的大型鸟群的行为特征。管理拓扑相互作用是一项重大挑战,因为在广泛的系统中识别近邻的计算成本很高。为了解决这个问题,我们提出了一种新颖的随机粒子法来模拟介观动力学,并利用二叉树的[数学]近邻搜索算法将识别近邻的计算成本从二次复杂度降低到对数复杂度。最后,我们针对不同场景进行了各种数值实验,以验证算法的有效性,并研究了二维和三维的集体动力学。
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Kinetic Description of Swarming Dynamics with Topological Interaction and Transient Leaders
Multiscale Modeling &Simulation, Volume 22, Issue 3, Page 1169-1195, September 2024.
Abstract. In this paper, we present a model describing the collective motion of birds. The model introduces spontaneous changes in direction which are initialized by few agents, here referred to as leaders, whose influence acts on their nearest neighbors, in the following referred to as followers. Starting at the microscopic level, we develop a kinetic model that characterizes the behavior of large flocks with transient leadership. One significant challenge lies in managing topological interactions, as identifying nearest neighbors in extensive systems can be computationally expensive. To address this, we propose a novel stochastic particle method to simulate the mesoscopic dynamics and reduce the computational cost of identifying closer agents from quadratic to logarithmic complexity using a [math]-nearest neighbors search algorithm with a binary tree. Finally, we conduct various numerical experiments for different scenarios to validate the algorithm’s effectiveness and investigate collective dynamics in both two and three dimensions.
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