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Cited by 12Modular Robots and Swarm IntelligenceEvacuation and Crowd DynamicsDistributed Control Multi-Agent Systems

How individual interactions control aggregation patterns in gregarious arthropods

Gautrais, Jacques, Jost, Christian, Jeanson, Raphael, Theraulaz, Guy·2004·Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems
DOI 10.1075/is.5.2.05gau
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Abstract

Aggregation is one of the most widespread phenomena in animal groups and often represents a collective dynamic response to environmental conditions. In social species the underlying mechanisms mostly obey self-organized principles. This phenomenon constitutes a powerful model to decouple purely social components from ecological factors. Here we used a model of cockroach aggregation to address the problems of sensitivity of collective patterns and control of aggregation dynamics. The individual behavioural rules (as a function of neighbour density) and the emergent collective patterns were previously quantified and modelled by Jeanson et al. (2003, 2004). We first present the diverse spatio-temporal patterns of a derived model in response to parameter changes, either involving social or non-social interactions. This sensitivity analysis is then extended to evaluate the evolution of these patterns in mixed societies of sub-populations with different behavioural parameters. Simple linear or highly non-linear collective responses emerge. We discuss their potential application to control animal populations by infiltration of biomimetic autonomous robots that mimic cockroach behaviour. We suggest that detailed behavioural models are a prerequisite to do so.

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  • Early identification of disease outbreaks within a crop field requires information sharing between robots to make global patterns emerge from coupled local views, supporting suitable responses and better strategic planning.

    “For instance, early identification of the outbreak of diseases within a crop field requires information sharing between robots to make global patterns emerge from coupled local views, supporting suitable responses and better strategic planning [95], [125].”

    From Swarm Robotics: Past, Present, and Future [Point of View] (2021) · cites this paper as [95]

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Authors
Gautrais, J., Jost, C., Jeanson, R., & Theraulaz, G.
Affiliations
  • Université Paul Sabatier
  • Université Toulouse III - Paul Sabatier (FR)
ORCID
Jost, Christian
Venue
Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systems
Publisher
John Benjamins Publishing Company
Published
2004-09-06
Volume
5
Issue
2
Pages
245-269
ISSN
  • 1572-0373 (ISSN-L)
  • 1572-0381
DOI
10.1075/is.5.2.05gau
OpenAlex
W1998263338
Cited by
12
References
20
Citations by year
2025: 1 · 2023: 1 · 2021: 1 · 2020: 1 · 2015: 1 · 2014: 1
FWCI
3.55
Type
journal article
Language
en
Open access
closed
Locations
Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems (publishedVersion)
Topics
  • Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
  • Physical Sciences › Engineering › Ocean Engineering › Evacuation and Crowd Dynamics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
Keywords
animal aggregation, collective dynamics, self-organization, neighbor density, behavioral rules, emergent patterns, sensitivity analysis, mixed populations, biomimetic robots, population control, swarm robotics

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