A simple mechanism for collective decision-making in the absence of payoff information

Daniele Carlesso*, Justin M. McNab, Christopher J. Lustri, Simon Garnier, Chris R. Reid

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Animals are often faced with time-critical decisions without prior information about their actions’ outcomes. In such scenarios, individuals budget their investment into the task to cut their losses in case of an adverse outcome. In animal groups, this may be challenging because group members can only access local information, and consensus can only be achieved through distributed interactions among individuals. Here, we combined experimental analyses with theoretical modeling to investigate how groups modulate their investment into tasks in uncertain conditions. Workers of the arboreal weaver ant Oecophylla smaragdina form three-dimensional chains using their own bodies to bridge vertical gaps between existing trails and new areas to explore. The cost of a chain increases with its length because ants participating in the structure are prevented from performing other tasks. The payoffs of chain formation, however, remain unknown to the ants until the chain is complete and they can explore the new area. We demonstrate that weaver ants cap their investment into chains, and do not form complete chains when the gap is taller than 90 mm. We show that individual ants budget the time they spend in chains depending on their distance to the ground, and propose a distance-based model of chain formation that explains the emergence of this tradeoff without the need to invoke complex cognition. Our study provides insights into the proximate mechanisms that lead individuals to engage (or not) in collective actions and furthers our knowledge of how decentralized groups make adaptive decisions in uncertain conditions.

Original languageEnglish
Article numbere2216217120
Pages (from-to)1-11
Number of pages11
JournalProceedings of the National Academy of Sciences of the United States of America
Volume120
Issue number29
Early online date10 Jul 2023
DOIs
Publication statusPublished - 18 Jul 2023

Bibliographical note

Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • self-assembly
  • collective behavior
  • collective decision-making
  • uncertainty
  • swarm intelligence

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