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Simulating the evolution of recruitment behavior in foraging Ants


Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/12049

Simulating the evolution of recruitment behavior in foraging Ants

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dc.contributor.author Letendre, Kenneth
dc.date.accessioned 2011-02-08T20:34:12Z
dc.date.available 2011-02-08T20:34:12Z
dc.date.issued 2011-02-08
dc.date.submitted December 2010
dc.identifier.uri http://hdl.handle.net/1928/12049
dc.description.abstract Spatial heterogeneity in the distribution of food is an important determinant of species' optimal foraging strategies, and of the dynamics of populations and communities. In order to explore the interaction of food heterogeneity and colony size in their effects on the behavior of foraging ant colonies, we built agent-based models of the foraging and recruitment behavior of harvester ants of the genus Pogonomyrmex. We optimized the behavior of these models using genetic algorithms over a variety of food distributions and colony sizes, and validated their behavior by comparison with data collected on harvester ants foraging for seeds in the field. We compared two models: one in which ants lay a pheromone trail each time they return to the nest with food; and another in which ants lay pheromone trails selectively, depending on the density of other food available in the area where food was found. We found that the density-dependent trail-laying model fit the field data better. We found that in this density-dependent recruitment model, colonies of all sizes evolved intense recruitment behavior, even when optimized for environments in which the majority of foods are distributed homogeneously. We discuss the implications of these models to the understanding of optimal foraging strategy and community dynamics among ants, and potential for application to ACO and other distributed problem-solving systems. en_US
dc.description.sponsorship Sandia National National Laboratories, Graduate Research Fellowship LDRD 09-1292 en_US
dc.language.iso en en_US
dc.subject Ants,Distributed-Problem Solving,Foraging,Genetic Algorithm,Optimization,Recruitment en_US
dc.subject.lcsh Harvester ants--Food--Computer simulation.
dc.subject.lcsh Recruitment (Population biology)--Computer simulation.
dc.subject.lcsh Distributed cognition--Animal models.
dc.subject.lcsh Genetic algorithms.
dc.title Simulating the evolution of recruitment behavior in foraging Ants en_US
dc.type Thesis en_US
dc.description.degree Computer Science en_US
dc.description.level Masters en_US
dc.description.department University of New Mexico. Dept. of Computer Science en_US
dc.description.advisor Moses, Melanie
dc.description.committee-member Forrest, Stephanie
dc.description.committee-member Watson, Paul

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