An illative network for robot learning based on the improved perceptron

Abstract

Based on the principle of multilayer perceptron (MLP), we present a new algorithm with adaptive learning rate factors for the improvement of MLP learning. The improved algorithm is applied to the learning of an illative network for the escaping process of robot. The simulations show the improved algorithm has good effects on speeding up learning process and bettering its learning convergence and robust performance.