Collective decision making in dynamic environments

Article


Prasetyo, J., De Masi, G. and Ferrante, E. 2019. Collective decision making in dynamic environments. Swarm Intelligence. 13 (3-4), pp. 217-243. https://doi.org/10.1007/s11721-019-00169-8
TypeArticle
TitleCollective decision making in dynamic environments
AuthorsPrasetyo, J., De Masi, G. and Ferrante, E.
Abstract

Collective decision making is the ability of individuals to jointly make a decision without any centralized leadership, but only relying on local interactions. A special case is represented by the best-of-n problem, whereby the swarm has to select the best option among a set of n discrete alternatives. In this paper, we perform a thorough study of the best-of-n problem in dynamic environments, in the presence of two options (n=2). Site qualities can be directly measured by agents, and we introduce abrupt changes to these qualities. We introduce two adaptation mechanisms to deal with dynamic site qualities: stubborn agents and spontaneous opinion switching. Using both computer simulations and ordinary differential equation models, we show that: (i) The mere presence of the stubborn agents is enough to achieve adaptability, but increasing its number has detrimental effects on the performance; (ii) the system adaptation increases with increasing swarm size, while it does not depend on agents’ density, unless this is below a critical threshold; (iii) the spontaneous switching mechanism can also be used to achieve adaptability to dynamic environments, and its key parameter, the probability of switching, can be used to regulate the trade-off between accuracy and speed of adaptation.

KeywordsDynamic environments; Collective decision making; Best-of-n; Swarm robotics; Complex adaptive systems
PublisherSpringer
JournalSwarm Intelligence
ISSN1935-3812
Electronic1935-3820
Publication dates
Online26 Jun 2019
Print31 Dec 2019
Publication process dates
Deposited26 Jun 2020
Accepted15 Jun 2019
Output statusPublished
Publisher's version
License
Copyright Statement

© The Author(s) 2019
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Digital Object Identifier (DOI)https://doi.org/10.1007/s11721-019-00169-8
Scopus EID2-s2.0-85068225203
Web of Science identifierWOS:000495817800004
LanguageEnglish
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