A bio-inspired spatial defence strategy for collective decision making in self-organized swarms

Prasetyo, Judhi, De Masi, Giulia, Zakir, Raina, Alkilabi, Muhanad, Tuci, Elio and Ferrante, Eliseo (2021) A bio-inspired spatial defence strategy for collective decision making in self-organized swarms. GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference. In: GECCO 2021, 10-14 Jul 2021, Lille, France. ISBN 9781450383509. [Conference or Workshop Item] (doi:10.1145/3449639.3459356)

Abstract

In collective decision-making, individuals in a swarm reach consensus on a decision using only local interactions without any centralized control. In the context of the best-of-n problem - characterized by n discrete alternatives - it has been shown 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 to modulate positive feedback, long dissemination times could potentially also be used in an adversarial way, whereby adversarial swarms could infiltrate the system and propagate bad decisions using aggressive dissemination strategies. Motivated by the above scenario, in this paper we propose a bio-inspired defence strategy that allows the swarm to be resilient against options that can be disseminated for longer times. This strategy mainly consists in reducing the mobility of the agents that are associated to options disseminated for a shorter amount of time, allowing the swarm to converge to this option. We study the effectiveness of this strategy using 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.

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