Self-Organization In 1-d Swarm Dynamics

TL;DR

This paper investigates how a one-dimensional swarm of agents self-organizes into subgroups with different velocities, influenced by initial conditions and local interactions, using a mean field model.

Contribution

It introduces a mean field phase space model for 1D swarm dynamics that explains the emergence of subgroup division based on initial scale parameters.

Findings

Group-division depends on initial position and velocity scales.

Comparison shows differences from fixed-speed and consensus-based models.

Self-organization occurs through local velocity averaging.

Abstract

Self-organization of a biologically motivated swarm into smaller subgroups of different velocities is found by solving a 1-dimensional adaptive-velocity swarm, in which the velocity of an agent is averaged over a finite local radius of influence. Using a mean field model in phase space, we find a dependence of this group-division phenomenon on the typical scales of the initial swarm in the position and velocity dimensions. Comparisons are made to previous swarm models in which the speed of an agent is either fixed or adjusted according to the degree of direction consensus among its local neighbors. Key words: self-organization of swarm, phase space, multi-agent system, dynamical system, group-division.