Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractcDNA cloning and physical mapping of porcine 3 beta-hydroxysteroid dehydrogenase/Delta 5-Delta 4 isomerase    Next AbstractAnalysis by desorption of volatile impurities from an ionic liquid solution in an unmodified gas chromatograph inlet »

J Theor Biol


Title:Modeling shortest path selection of the ant Linepithema humile using psychophysical theory and realistic parameter values
Author(s):von Thienen W; Metzler D; Witte V;
Address:"Fakultat fur Biologie, Department Biologie II, Ludwig-Maximilians Universitat Munchen, Grosshaderner Str. 2, D-82152 Planegg, Germany. Electronic address: w@thienen.de. Fakultat fur Biologie, Department Biologie II, Ludwig-Maximilians Universitat Munchen, Grosshaderner Str. 2, D-82152 Planegg, Germany. Electronic address: metzler@bio.lmu.de. Fakultat fur Biologie, Department Biologie II, Ludwig-Maximilians Universitat Munchen, Grosshaderner Str. 2, D-82152 Planegg, Germany. Electronic address: witte@bio.lmu.de"
Journal Title:J Theor Biol
Year:2015
Volume:20150311
Issue:
Page Number:168 - 178
DOI: 10.1016/j.jtbi.2015.02.030
ISSN/ISBN:1095-8541 (Electronic) 0022-5193 (Linking)
Abstract:"The emergence of self-organizing behavior in ants has been modeled in various theoretical approaches in the past decades. One model explains experimental observations in which Argentine ants (Linepithema humile) selected the shorter of two alternative paths from their nest to a food source (shortest path experiments). This model serves as an important example for the emergence of collective behavior and self-organization in biological systems. In addition, it inspired the development of computer algorithms for optimization problems called ant colony optimization (ACO). In the model, a choice function describing how ants react to different pheromone concentrations is fundamental. However, the parameters of the choice function were not deduced experimentally but freely adapted so that the model fitted the observations of the shortest path experiments. Thus, important knowledge was lacking about crucial model assumptions. A recent study on the Argentine ant provided this information by measuring the response of the ants to varying pheromone concentrations. In said study, the above mentioned choice function was fitted to the experimental data and its parameters were deduced. In addition, a psychometric function was fitted to the data and its parameters deduced. Based on these findings, it is possible to test the shortest path model by applying realistic parameter values. Here we present the results of such tests using Monte Carlo simulations of shortest path experiments with Argentine ants. We compare the choice function and the psychometric function, both with parameter values deduced from the above-mentioned experiments. Our results show that by applying the psychometric function, the shortest path experiments can be explained satisfactorily by the model. The study represents the first example of how psychophysical theory can be used to understand and model collective foraging behavior of ants based on trail pheromones. These findings may be important for other models of pheromone guided ant behavior and might inspire improved ACO algorithms"
Keywords:"Algorithms Animals Ants/*physiology Behavior, Animal Computer Simulation *Feeding Behavior Models, Biological Monte Carlo Method Pheromones/*physiology Probability Psychometrics Psychophysics *Social Behavior Ant behavior Ant colony optimization (ACO) Phe;"
Notes:"Medlinevon Thienen, Wolfhard Metzler, Dirk Witte, Volker eng England 2015/03/15 J Theor Biol. 2015 May 7; 372:168-78. doi: 10.1016/j.jtbi.2015.02.030. Epub 2015 Mar 11"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 27-12-2024