Abstract
Abstract This paper introduces a connectionist model of cognitive map formation and use which performs wayfinding tasks. This model is at a higher level of cognitive function than much connectionist work. Its units are each at the level of an already trained backpropagation pattern recognizer. Although similar in certain respects to Hendler's work, the model described herein offers several additional features: first, it is a connectionist model; secondly it learns relationships via a modified Hebbian learning rule and so does not need to input a database; thirdly, spreading activation is an integral part of the model. The model introduced here also differs from backpropagation models in two important respects. First, it does not require correct training input; rather, it learns from ordinary experience. Secondly, it does not converge to a fixed point or equilibrium state; thus, more sophisticated mechanisms are required to control the network's activity. Fatigue and three types of inhibition combine to ca...
Published Version
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