Neural network training using the constructivism paradigms

Abstract

The Backpropagation Algorithm (BA) is the standard method for training multilayer Artificial Neural Networks (ANN), although it converges very slowly and can stop in a local minimum. We present a new method for neural network training using the BA inspired on constuctivism, an alphabetization method proposed by Emilia Ferreiro (1985) based on Piaget philosophy. Simulation results show that the proposed configuration usually obtained a lower final mean square error, when compared with the standard BA and with the BA with momentum factor.