The best-of-n problem with dynamic site qualities: Achieving adaptability with stubborn individuals

X JUDHI PRASETYO, Giulia De Masi, Pallavi Ranjan, Eliseo Ferrante

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Collective decision-making is one of main building blocks of swarm robotics collective behaviors. It is the ability of individuals to make a collective decision without any centralized leadership, but only via local interaction and communication. The best-of-n problem is a subclass of collective decision-making, whereby the swarm has to select the best option among a set of n possible alternatives. Recently, the best-of-n problems has gathered momentum: a number of decision-making mechanisms have been studied focusing both on cases where there is an explicit measurable difference between the two qualities, as well as on cases when there are only delay costs in the environment driving the consensus to one of the n alternatives. To the best of our knowledge, all the formal studies on the best-of-n problem have considered a site quality distribution that is stationary and does not change over time. In this paper, we perform a study of the best-of-n problems in a dynamic environment setting. We consider the situation where site qualities can be directly measured by agents, and we introduce abrupt changes to these qualities, whereby the two qualities are swapped at a given time. Using computer simulations, we show that a vanilla application of one of the most studied decision-making mechanism, the voter model, does not guarantee adaptation of the swarm consensus towards the best option after the swap occurs. Therefore, we introduce the notion of stubborn agents, which are not allowed to change their opinion. We show that the presence of the stubborn agents is enough to achieve adaptability to dynamic environments. We study the performance of the system with respect to a number of key parameters: the swarm size, the difference between the two qualities and the proportion of stubborn individuals.

langue originaleAnglais
titreSwarm Intelligence - 11th International Conference, ANTS 2018, Proceedings
rédacteurs en chefChristian Blum, Anders L. Christensen, Vito Trianni, Andreagiovanni Reina, Marco Dorigo, Mauro Birattari
EditeurSpringer Verlag
Nombre de pages13
ISBN (imprimé)9783030005320
Les DOIs
Etat de la publicationPublié - 2018
Evénement11th International Conference on Swarm Intelligence, ANTS 2018 - Rome, Italie
Durée: 29 oct. 201831 oct. 2018

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11172 LNCS
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence11th International Conference on Swarm Intelligence, ANTS 2018
La villeRome

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