Research Article: How does the interaction radius affect the performance of intervention on collective behavior?

Date Published: February 15, 2018

Publisher: Public Library of Science

Author(s): Caiyun Wang, Jing Han, Andrew Baggaley.

http://doi.org/10.1371/journal.pone.0192738

Abstract

The interaction radius r plays an important role in the collective behavior of many multi-agent systems because it defines the interaction network among agents. For the topic of intervention on collective behavior of multi-agent systems, does r also affect the intervention performance? In this paper we study whether it is easier to change the convergent heading of the group by adding some special agents (called shills) into the Vicsek model when r is larger (or smaller). Two kinds of shills are considered: fixed-heading shills (like leaders that never change their headings) and evolvable-heading shills (like normal agents but with carefully designed initial headings). We know that with the increase of r, two contradictory effects exist simultaneously: the influential area of a single shill is enlarged, but its influence strength is weakened. Which factor dominates? Through simulations and theoretical analysis we surprisingly find that r affects the intervention performance differently in different cases: when fixed-heading shills are placed together at the center of the group, larger r gives a better intervention performance; when evolvable-heading shills are placed together at the center, smaller r is better; when shills (either fixed-heading or evolvable-heading) are distributed evenly inside the group, the effect of r on the intervention performance is not significant. We believe these results will inspire the design of intervention strategies for many other multi-agent systems.

Partial Text

In recent years, collective behavior has drawn a lot of attention from scientists in many areas. It is a significant feature of self-organized multi-agent systems (MASs) where agents usually interact with each other based on local rules, i.e., each agent interacts with its neighbors. At the macroscopic level, new phenomenon will emerge in MASs which can not be found in a single agent, such as flocking of birds [1, 2], schooling of fishes [1], crowd panic [3], swarm intelligence [4], pattern formation [5, 6], synchronization [7–9], etc.

To study effects of interaction radius on the soft control performance based on the Vicsek model, a number of simulations are performed for four combinations of two strategies (centered and distributed) in two scenarios (fixed-heading-shill and evolvable-heading-shill). And then we extend this study to the linearized Vicsek model and the non-periodic boundary model cases. Some related discussions and theoretical analysis are given.

Based on a classic multi-agent system model, the Vicsek model, we study the effect of the interaction radius on the soft control performance. Then we extend the approach to the linearized Vicsek model and the non-periodic boundary model cases. We consider two different soft control strategies (centered and distributed) in two scenarios (fixed-heading-shill or evolvable-heading-shill). We obtain the following results (see Fig 9 for details) through simulations and analysis:

 

Source:

http://doi.org/10.1371/journal.pone.0192738

 

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