A Bio-Inspired Spatial Defence Strategy for Collective Decision Making in Self-Organized Swarms

X JUDHI PRASETYO, Giulia De Masi, Raina Zakir, Muhanad Hayder Mohammed Alkilabi, Elio Tuci, Eliseo Ferrante

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In collective decision-making, individuals in a swarm reach consensus on adecision using only local interactions without any centralized control. In the con-text of the best-of-n problem - characterized by n discrete alternatives - it has beenshown that consensus to the best option can be reached if individuals disseminate that option more than the other options. Besides being used as a mechanism tomodulate positive feedback, long dissemination times could potentially also beused in an adversarial way, whereby adversarial swarms could infiltrate the systemand propagate bad decisions using aggressive dissemination strategies. Motivatedby the above scenario, in this paper we propose a bio-inspired defence strategythat allows the swarm to be resilient against options that can be disseminated forlonger times. This strategy mainly consists in reducing the mobility of the agentsthat are associated to options disseminated for a shorter amount of time, allowingthe swarm to converge to this option. We study the effectiveness of this strategyusing two classical decision mechanisms, the voter model and the majority rule,showing that the majority rule is necessary in our setting for this strategy to work.The strategy has also been validated on a real Kilobots experiment.
Original languageEnglish
Title of host publicationProceedings of the Genetic and Evolutionary Computation Conference (GECCO)
PublisherACM Press
Publication statusPublished - 2021
EventGECCO '21: Genetic and Evolutionary Computation Conference - Lille, France
Duration: 10 Jul 202114 Jul 2021
Conference number: 21


ConferenceGECCO '21: Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO


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