An approach to encode multilayer perceptrons

Abstract

Genetic connectionism is based on the integration of evolution and neural network learning within one system. An overview of the Multilayer Perceptron encoding schemes is presented. A new approach is shown and tested on various case studies. The proposed genetic search not only optimizes the network topology but shortens the training time. There is no doubt that genetic algorithms can be used to solve efficiently the problem of network optimization considering not only static aspects of network architecture but also dynamic ones. © Springer-VerlagBerlin Heidelberg 2002.