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Related Experiment Video

Updated: Jul 18, 2026

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats

Published on: January 18, 2013

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

Caiyun Wang^1,2, Jing Han^1,2

¹LSC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.

|February 16, 2018

Summary

The interaction radius (r) in multi-agent systems impacts intervention performance. Larger r benefits fixed-heading shills, while smaller r aids evolvable-heading shills, depending on placement.

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Area of Science:

Complex Systems
Agent-Based Modeling
Collective Behavior

Background:

The interaction radius (r) is crucial for defining agent networks in multi-agent systems.
Understanding how 'r' influences intervention performance is key for controlling collective behavior.

Purpose of the Study:

To investigate the effect of interaction radius (r) on intervention performance in the Vicsek model.
To determine if larger or smaller 'r' values improve the effectiveness of shills in altering group heading.

Main Methods:

Simulations of the Vicsek model with varying interaction radii (r).
Introduction of two types of shills: fixed-heading and evolvable-heading.
Theoretical analysis to complement simulation findings.

Main Results:

Larger 'r' improves intervention with centrally placed fixed-heading shills.
Smaller 'r' enhances intervention with centrally placed evolvable-heading shills.
Distributed shills show insignificant 'r' dependency for intervention performance.

Conclusions:

The impact of interaction radius on intervention is nuanced and depends on shill type and placement.
Findings offer insights for designing effective intervention strategies in diverse multi-agent systems.