Simulating the evolution of ant behaviour in evaluating nest sites

James A.R. Marshall, Tim Kovacs, Anna R. Dornhaus, Nigel R. Franks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations


When an ant colony needs to find a new nest, scouts are sent out to evaluate the suitability of potential sites, particularly their size. It has been suggested that ant scouts of Leptothorax albipennis use a simple heuristic known as Buffon's needle to evaluate nest size. They do this in two stages: first laying a pheromone trail in the nest site, then, after a return to the old nest, coming back and wandering within the site assessing frequency of intersection with the pheromone trail ("two-pass" strategy). If a colony is forced to relocate from its current nest due to destruction of that nest, the time required to find a suitable new nest may be crucial. This paper details preliminary results from a computer simulation model of evaluation of nest size. The model aims to study why a "two-pass" strategy is used by ants when a "one-pass" strategy, in which the ant simultaneously lays pheromone and assesses the frequency at which it encounters its own trail, may be more time efficient. Analysis of the results indicates no clear advantage for the "two-pass" strategy, given the assumptions of the model. Possible implications of this result are discussed.

Original languageEnglish (US)
Title of host publicationAdvances in Artificial Life
EditorsWolfgang Banzhaf, Jens Ziegler, Thomas Christaller, Peter Dittrich, Jan T. Kim
Number of pages8
ISBN (Print)3540200576, 9783540200574
StatePublished - 2003
Event7th European Conference on Artificial Life, ECAL 2003 - Dortmund, Germany
Duration: Sep 14 2003Sep 17 2003

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
ISSN (Print)0302-9743


Conference7th European Conference on Artificial Life, ECAL 2003

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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