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Communication Dans Un Congrès Année : 2002

A new clustering algorithm based on the chemical recognition system of ants

Résumé

In this paper, we introduce a new method to solve the unsupervised clustering problem, based on a modelling of the chemical recognition system of ants. This system allow ants to discriminate between nestmates and intruders , and thus to create homogeneous groups of individuals sharing a similar odor by continuously exchanging chemical cues. This phenomenon, known as " colonial closure " , inspired us into developing a new clustering algorithm and then comparing it to a well-known method such as K-MEANS method. Our results show that our algorithm performs better than K-MEANS over artificial and real data sets, and furthermore our approach requires less initial information (such as number of classes, shape of classes, limitation in the types of attributes handled).
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Dates et versions

hal-01247362 , version 1 (21-12-2015)

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  • HAL Id : hal-01247362 , version 1

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Nicolas Labroche, Nicolas Monmarché, Gilles Venturini. A new clustering algorithm based on the chemical recognition system of ants. European Conference on Artificial Intelligence, Jul 2002, Lyon, France. ⟨hal-01247362⟩
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