Consensus or Deadlock? Consequences of Simple Behavioral Rules for Coordination in Group Decisions.
Coordinated collective behaviors often emerge from simple rules governing the interactions of individuals in groups. We model mechanisms of coordination among ants during cooperative transport, a challenging task that requires a consensus on travel direction. Our goal is to determine whether groups following simple behavioral rules can reach a consensus using minimal information. Using deterministic and stochastic models, we investigate behavioral factors that affect coordination. We define and investigate three types of behavioral rules governing individual behavior that differ in the information available: individuals either 1) have no information, 2) can measure transport success, or 3) measure success while also knowing whether they are aligned with the majority. We find that groups break deadlocks only if individuals more readily give up when they are going against the majority, corresponding to rule type 3 -such groups are "informed." These behavioral rules succeed through positive and negative feedbacks that are implemented in our model via a single mechanism: individuals only need to measure the relative group sizes to make effective decisions. We also find that groups reach consensus more quickly if they have either a shared bias, high sensitivity to group behavior, or finely tuned persistence. Each of these is a potential adaptation for efficient cooperative transport. This flexibility makes the behavioral rules in the informed case relatively robust to deficiencies in the individuals' capabilities. While inspired by ants, our results are generalizable to other collective decisions with deadlocks, and demonstrate that groups of behaviorally simple individuals with no memory and extremely limited information can break symmetry and reach a consensus in a decision between two equal options.
Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, United States of America.
Helen F
HF
McCreery
Department of Computer Science, University of Colorado, Boulder, Colorado, United States of America.
Nikolaus
N
Correll
Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, United States of America.
Michael D
MD
Breed
Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, United States of America.
Samuel
http://orcid.org/0000-0002-6238-1174
S
Flaxman
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