KohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern Classification

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dc.creatorFernandes, C.
dc.creatorMora, A. M.
dc.creatorMerelo, J. J.
dc.creatorRamos, V.
dc.creatorLaredo, J. L. J.
dc.date2008-03-18
dc.date.accessioned2026-07-07T09:27:23Z
dc.date.available2026-07-07T09:27:23Z
dc.descriptionIn this paper we introduce a new ant-based method that takes advantage of the cooperative self-organization of Ant Colony Systems to create a naturally inspired clustering and pattern recognition method. The approach considers each data item as an ant, which moves inside a grid changing the cells it goes through, in a fashion similar to Kohonen's Self-Organizing Maps. The resulting algorithm is conceptually more simple, takes less free parameters than other ant-based clustering algorithms, and, after some parameter tuning, yields very good results on some benchmark problems.
dc.descriptionSubmitted to ALIFE XI
dc.identifierhttps://arxiv.org/abs/0803.2695
dc.identifierhttp://arxiv.org/abs/0803.2695
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/157085
dc.subjectNeural and Evolutionary Computing
dc.subjectComputer Vision and Pattern Recognition
dc.titleKohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern Classification
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