2008/03/18 by Carlos M. Fernandes, Antonio M. Mora, Fernandes, C. +7
Computer Science · #Neural Networks and Applications #Metaheuristic Optimization Algorithms Research #Evolutionary Algorithms and Applications
paper · pdf · doi:10.48550/arxiv.0803.2695
In 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.