An agent-based model of nest-site selection in a mass -recruiting ant
Authored by Adam L Cronin
Date Published: 2018
DOI: 10.1016/j.jtbi.2018.07.004
Sponsors:
No sponsors listed
Platforms:
NetLogo
Model Documentation:
ODD
Flow charts
Model Code URLs:
https://ars-els-cdn-com.ezproxy1.lib.asu.edu/content/image/1-s2.0-S0022519318303175-mmc1.docx
Abstract
Complex systems are modular entities which can collectively generate
sophisticated emergent solutions through interactions based on simple,
local rules. In this study, I use an agent-based model to elucidate how
numerous individual-level components contribute to the collective
decision process during house hunting in a mass-recruiting ant species.
Myrmecina nipponica combines the use of pheromone trails with a quorum
decision rule in collective decisions among nest sites when searching
for a new home. The model employed only individual-level rules but
accurately emulated group-level properties observed in empirical
studies. Simulations suggest that in this system i) both social and
private information are necessary for effective decision making, ii)
decision making was effective even with very low numbers of
`discriminating' individuals, iii) individual acceptance thresholds were
more influential than quorum thresholds in tuning decisions to emphasise
speed or accuracy, and iv) acceptance thresholds could also help tune
decisions to suit environmental complexity. Similar findings in species
using one-to-one recruitment suggest that some individual parameters,
such as acceptance thresholds, may hold key functions in collective
decision making regardless of the form of recruitment. (C) 2018 Elsevier
Ltd. All rights reserved.
Tags
Swarm intelligence
emergence
Quorum sensing
collective decision-making
information
Organization
Individuals
Honeybee swarms
Trade-offs
Speed
Temnothorax-albipennis
Myrmecina-nipponica
Pheromone trails