基于粒子群优化的集体运动主体自组织:定性分析

Armando Serrato Barrera, A. López-López, G. Gómez
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引用次数: 4

摘要

在过去的几十年里,已经有几种方法对羊群、牛群和鱼群的集体行为进行了建模。近年来,使用基于粒子群优化算法(PSO)的简单模型获得了类似的行为。在本文中,我们对这种方法进行了定性分析。并将其与基于Reynolds规则和势函数格式的经典模型进行了比较。最后给出了实现细节和仿真结果。本研究的最终目标是利用粒子群算法对多目标群集进行建模。我们提供了我们如何设想这一点的总体概述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-organization of agents for collective movement based on particle swarm optimization: A qualitative analysis
Collective behavior of flocks, herds and schools of fish has been modeled by several approaches in the last decades. In recent years, similar behavior has been obtained by using a simple model based on particle swarm optimization algorithm (PSO). In this article we provide a qualitative analysis of this approach. We also compare it with classical models based on Reynolds rules and potential functions schemes. Furthermore, implementation details and simulation results are given. The final goal of this study is to model multi-target flocking using PSO approach. We provide a general overview of how we envision this.
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