Diverse stochasticity leads a colony of ants to optimal foraging

Masashi Shiraishi, Rito Takeuchi, Hiroyuki Nakagawa, Shin I. Nishimura, Akinori Awazu, Hiraku Nishimori

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A mathematical model of garden ants (Lasius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when the variance in the sensitivity to pheromone for ants is introduced in the model.

Original languageEnglish
Pages (from-to)7-16
Number of pages10
JournalJournal of Theoretical Biology
Volume465
DOIs
Publication statusPublished - 21 Mar 2019

Keywords

  • Ants
  • Collective motion
  • Optimization
  • Stochastic foraging

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