Self-organization of agents for collective movement based on particle swarm optimization: A qualitative analysis

Abstract

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.