This work focus on the problem of automatic generation of fuzzy systems by means of evolutionary computation, specifically using the approach of coevolution. Co-evolution is based on the idea of modular modeling of the problem subcomponents. In this work the subcomponents are represented by species, which have a collaborative relation among them. The fuzzy system to be created performs fuzzy pattern classification. Basically, the environment is composed by four different species, which have a hierarchical collaboration both in the generation of the species and in the fitness determination of the individuals of these species. These species are organized in levels, where the contribution in the specie generation happens from the lowest to highest levels and the contribution in the fitness determination happens from the highest to lowest levels. The fitness calculation includes evaluations of rules compactness, what was demonstrated to improve the system interpretability.
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