KANTS: Artifical Ant System for Classification

Authors:
Carlos Fernandes;Antonio Miguel Mora;Juan Julián Merelo;Vitorino Ramos;Juan Luís Laredo;Agostihno Rosa
Affiliations:
LASEEB-ISR/IST, University of Lisbon, Portugal and Dep. de Arquitectura y Tecnología de Computadores, University of Granada, Spain;Dep. de Arquitectura y Tecnología de Computadores, University of Granada, Spain;Dep. de Arquitectura y Tecnología de Computadores, University of Granada, Spain;LASEEB-ISR/IST, University of Lisbon, Portugal;Dep. de Arquitectura y Tecnología de Computadores, University of Granada, Spain;LASEEB-ISR/IST, University of Lisbon, Portugal
Venue:
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
Year:
2008

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Abstract

This paper investigates a new model that takes advantage of the cooperative self-organization of Ant Algorithms to evolve a naturally inspired pattern recognition (and also clustering) method. The approach considers each data item as an ant that changes the environment as it moves through it. The algorithm is successfully applied to well-known classification problems and yields better results than some other classification approaches, like K-Nearest Neighbours and Neural Networks.