Evolutionary Methods to Create Interpretable Modular System

Authors:
Marcin Korytkowski;Marcin Gabryel;Leszek Rutkowski;Stanislaw Drozda
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland 42-200 and The Professor Kotarbinski Olsztyn Academy of Computer Science and Management, Olsztyn, Pola ...;Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland 42-200 and The Professor Kotarbinski Olsztyn Academy of Computer Science and Management, Olsztyn, Pola ...;Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland 42-200 and Department of Artificial Intelligence, WSHE University in Łódź, Łó ...;The Faculty of Mathematics and Computer Sciences, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland 10-561 and The Professor Kotarbinski Olsztyn Academy of Computer Science and Managemen ...
Venue:
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Year:
2006

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Abstract

In this paper we present an evolutionary method to create an interpretable modular system. It consists of many neuro-fuzzy structures which are merged using a very popular algorithm called AdaBoost. As the alternative to the backpropagation method to train all models a special evolutionary algorithm has been used based on the evolutionary strategy (μ, 茂戮驴).