A cooperative evolutionary algorithm for classification
Cătălin Stoean, Ruxandra Stoean, Marcel Preuß, Dumitru Dumitrescu · Leiden Repository (Leiden University) · 2006
An evolutionary algorithm based on cooperative coevolution is applied to a classification problem, the Pima Indian diabetes diagnosis problem. Previous cooperative coevolution algorithms were developed for function optimization [1], optimizing agents behaviour [2] or modelling the behaviour of a robot in an unknown environment [3]. The aim of this paper is to integrate the cooperative approach into a learning classifier system and use it for solving a real-world problem of classification. To the best of our knowledge, there have been no attempts on applying cooperative coevolution specifically to classification. For each category of the classification problem, a sub-population evolves specific rules using a classical genetic algorithm. Sub-populations evolve simultaneously but independently; cooperation between them takes place only when the fitness of an individual in computed. Obtained experimental results encourage further investigation.