Guiding aggregation dynamics in a swarm of agents via informed individuals: an analytical study

Yannick Gillet, Eliseo Ferrante, Ziya FIRAT, Elio Tuci

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Abstract

Self-organised aggregation, the formation of large clustersof independent agents, is an important process in swarmrobotics systems since it is the prerequisite for more com-plex collective behaviours. Previous work on self-organisedaggregation focused on the study of the individual mecha-nisms required to allow a swarm to form a single aggregate.In this paper, we discuss an analytical model which looks atthe possibility to use the concept of informed individuals toallow the swarm to distribute on different aggregation sitesaccording to proportions of individuals at each site arbitrarilychosen by the designer. Informed individuals are opinionatedagents that selectively prefer an aggregation site and avoid torest on the non-preferred sites. We study environments withtwo aggregation sites, and consider two different scenarios:one in which the informed individuals are equally distributedin numbers between the two sites; and one in which informedindividuals for one type of site are three times more numer-ous than those on the other site. Our objective is to find outwhether and for what range of model parameters the swarmdistributes between the two sites according to the relative dis-tribution of informed agents among the two sites. The analy-sis of the model shows that the designer capability to exploitinformed individuals to control how the swarm aggregatesdepends on the environmental conditions. For intermediatevalues of the site carrying capacity, a small minority of in-formed individuals is able to guide the dynamics as desiredby the designer. We also show that the larger the site carryingcapacity the larger the total proportion of informed individu-als required to lead the swarm to the desired distribution ofindividuals between the two sites
Original languageEnglish
Title of host publicationProceedings of the 2019 Conference on Artificial Life
PublisherMIT Press
Pages590-597
Number of pages8
DOIs
Publication statusPublished - 2020
Event2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019 - Newcastle upon Tyne, United Kingdom
Duration: 29 Jul 20192 Aug 2019

Publication series

NameThe 2019 Conference on Artificial Life

Conference

Conference2019 Conference on Artificial Life: How Can Artificial Life Help Solve Societal Challenges, ALIFE 2019
Country/TerritoryUnited Kingdom
CityNewcastle upon Tyne
Period29/07/192/08/19

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