Introducing KohonAnts, a new stigmergic clustering and classification algorithm

We have submitted, and at the same time uploaded to ArXiV, a paper on this new algorithm the masterminds of GeNeura + Carlos Fernandes and Vitorino Ramos (who are practically now full-privileges GeNeura members). You can download it from ArXiV; the title is KohonAnts: A Self-Organizing Ant Algorithm for Clustering and Pattern Classification:

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.

We’ll be very soon doing the rounds with this algorithm with the usual conferences. It is new, it works surprisingly well, and, as usual, source code is available from your friendly Forja subversion repository (not updated, though).

One thought on “Introducing KohonAnts, a new stigmergic clustering and classification algorithm

  1. Pingback: Kohonants: a gentle introduction « GeNeura Team

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