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Updated: Jan 30, 2026

Collection and Long-Term Maintenance of Leaf-Cutting Ants Atta in Laboratory Conditions
Published on: August 30, 2022
Diverse stochasticity leads a colony of ants to optimal foraging
Masashi Shiraishi1, Rito Takeuchi2, Hiroyuki Nakagawa3
1Department of Mathematical and Life Sciences, Graduate School of Science, Hiroshima University, Kagamiyama, Higashi-hiroshima 739-8526, Japan; CREST, JST, Tokyo, Japan.
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.
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