A model for goal oriented learning in a neural network

Abstract

A mathematical model for goal oriented learning in a network of neuron-like elements was developed. Using a mouse/goal box analogy, a simulation of a network with four elements was programmed in Turbo Pascal, Version 4.0 (Borland International) to test the model. Each location in the network corresponded to a particular network input. The output of the network consisted of one of four behaviors: forward, backward, left or right. The network successfully learned sequences of up to six movements in increasingly complex mazes.