Analysis of ant foraging algorithms

N. F. Britton, T. R. Stickland, N. R. Franks

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

We consider some models of ant foraging and recruitment behaviour that depend on each individual ant following a simple algorithm. Self-organisation enables the colony as a whole to establish a foraging strategy in the absence of any hierarchical control. In this paper we investigate how the effectiveness of such a foraging strategy depends on the persistence of the signals used by the individual ants and on the errors they make in following such signals. The use of inhibitory as well as excitatory signals is considered, and shown to be extremely effective in certain circumstances. This is interesting, as such signals have never been observed in real ant colonies. Such models are often investigated by simulation, but we approach them from the point of view of statistical mechanics. Looked at another way, which yields some insight, we approximate the stochastic process that models the system by a diffusion process with small diffusion parameter. This approach does not replace simulation, but supplements it. Its advantage is that it can elucidate the role of parameters more clearly and using much less computer time than simulation, but its disadvantage is that many simplifying assumptions must be made before the problem is amenable to analytic treatment.

Original languageEnglish
Pages (from-to)315-336
Number of pages22
JournalJournal of Biological Systems
Volume6
Issue number4
Publication statusPublished - Dec 1998

Fingerprint

Ants
Foraging
ant
Formicidae
foraging
Statistical mechanics
stochastic processes
Stochastic Processes
simulation
Random processes
mechanics
Hierarchical Control
Simulation
self organization
stochasticity
Self-organization
Ant Colony
Mechanics
Statistical Mechanics
Computer Simulation

Keywords

  • Ants
  • Foraging
  • Self-organization
  • Signals

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Ecology
  • Applied Mathematics

Cite this

Britton, N. F., Stickland, T. R., & Franks, N. R. (1998). Analysis of ant foraging algorithms. Journal of Biological Systems, 6(4), 315-336.

Analysis of ant foraging algorithms. / Britton, N. F.; Stickland, T. R.; Franks, N. R.

In: Journal of Biological Systems, Vol. 6, No. 4, 12.1998, p. 315-336.

Research output: Contribution to journalArticle

Britton, NF, Stickland, TR & Franks, NR 1998, 'Analysis of ant foraging algorithms', Journal of Biological Systems, vol. 6, no. 4, pp. 315-336.
Britton NF, Stickland TR, Franks NR. Analysis of ant foraging algorithms. Journal of Biological Systems. 1998 Dec;6(4):315-336.
Britton, N. F. ; Stickland, T. R. ; Franks, N. R. / Analysis of ant foraging algorithms. In: Journal of Biological Systems. 1998 ; Vol. 6, No. 4. pp. 315-336.
@article{840695cd2c5d473ca5eceeb16d0ab465,
title = "Analysis of ant foraging algorithms",
abstract = "We consider some models of ant foraging and recruitment behaviour that depend on each individual ant following a simple algorithm. Self-organisation enables the colony as a whole to establish a foraging strategy in the absence of any hierarchical control. In this paper we investigate how the effectiveness of such a foraging strategy depends on the persistence of the signals used by the individual ants and on the errors they make in following such signals. The use of inhibitory as well as excitatory signals is considered, and shown to be extremely effective in certain circumstances. This is interesting, as such signals have never been observed in real ant colonies. Such models are often investigated by simulation, but we approach them from the point of view of statistical mechanics. Looked at another way, which yields some insight, we approximate the stochastic process that models the system by a diffusion process with small diffusion parameter. This approach does not replace simulation, but supplements it. Its advantage is that it can elucidate the role of parameters more clearly and using much less computer time than simulation, but its disadvantage is that many simplifying assumptions must be made before the problem is amenable to analytic treatment.",
keywords = "Ants, Foraging, Self-organization, Signals",
author = "Britton, {N. F.} and Stickland, {T. R.} and Franks, {N. R.}",
year = "1998",
month = "12",
language = "English",
volume = "6",
pages = "315--336",
journal = "Journal of Biological Systems",
issn = "0218-3390",
publisher = "World Scientific Publishing Co. Pte Ltd",
number = "4",

}

TY - JOUR

T1 - Analysis of ant foraging algorithms

AU - Britton, N. F.

AU - Stickland, T. R.

AU - Franks, N. R.

PY - 1998/12

Y1 - 1998/12

N2 - We consider some models of ant foraging and recruitment behaviour that depend on each individual ant following a simple algorithm. Self-organisation enables the colony as a whole to establish a foraging strategy in the absence of any hierarchical control. In this paper we investigate how the effectiveness of such a foraging strategy depends on the persistence of the signals used by the individual ants and on the errors they make in following such signals. The use of inhibitory as well as excitatory signals is considered, and shown to be extremely effective in certain circumstances. This is interesting, as such signals have never been observed in real ant colonies. Such models are often investigated by simulation, but we approach them from the point of view of statistical mechanics. Looked at another way, which yields some insight, we approximate the stochastic process that models the system by a diffusion process with small diffusion parameter. This approach does not replace simulation, but supplements it. Its advantage is that it can elucidate the role of parameters more clearly and using much less computer time than simulation, but its disadvantage is that many simplifying assumptions must be made before the problem is amenable to analytic treatment.

AB - We consider some models of ant foraging and recruitment behaviour that depend on each individual ant following a simple algorithm. Self-organisation enables the colony as a whole to establish a foraging strategy in the absence of any hierarchical control. In this paper we investigate how the effectiveness of such a foraging strategy depends on the persistence of the signals used by the individual ants and on the errors they make in following such signals. The use of inhibitory as well as excitatory signals is considered, and shown to be extremely effective in certain circumstances. This is interesting, as such signals have never been observed in real ant colonies. Such models are often investigated by simulation, but we approach them from the point of view of statistical mechanics. Looked at another way, which yields some insight, we approximate the stochastic process that models the system by a diffusion process with small diffusion parameter. This approach does not replace simulation, but supplements it. Its advantage is that it can elucidate the role of parameters more clearly and using much less computer time than simulation, but its disadvantage is that many simplifying assumptions must be made before the problem is amenable to analytic treatment.

KW - Ants

KW - Foraging

KW - Self-organization

KW - Signals

UR - http://www.scopus.com/inward/record.url?scp=0001252968&partnerID=8YFLogxK

M3 - Article

VL - 6

SP - 315

EP - 336

JO - Journal of Biological Systems

JF - Journal of Biological Systems

SN - 0218-3390

IS - 4

ER -