A novel artificial neural network trained using evolutionary algorithms for reinforcement learning

Abstract

This paper discusses the development of a novel pattern recognition system using artificial neural networks (ANNs) and evolutionary algorithms for reinforcement learning (EARL). The network is based on neuronal interactions involved in identification of prey and predator in toads. The distributed neural network (DNN) is capable of recognizing and classifying various features. The lateral inhibition between the output neurons helps the network in the classification process - similar to the gate in gating network. The results obtained are compared with standard neural network architectures and learning algorithms.