Philosophical Psychology 5 (2):199-219 (1992)

Abstract
This paper critically examines the claim that parallel distributed processing (PDP) networks are autonomous learning systems. A PDP model of a simple distributed associative memory is considered. It is shown that the 'generic' PDP architecture cannot implement the computations required by this memory system without the aid of external control. In other words, the model is not autonomous. Two specific problems are highlighted: (i) simultaneous learning and recall are not permitted to occur as would be required of an autonomous system; (ii) connections between processing units cannot simultaneously represent current and previous network activation as would be required if learning is to occur. Similar problems exist for more sophisticated networks constructed from the generic PDP architecture. We argue that this is because these models are not adequately constrained by the properties of the functional architecture assumed by PDP modelers. It is also argued that without such constraints, PDP researchers cannot claim to have developed an architecture radically different from that proposed by the Classical approach in cognitive science.
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DOI 10.1080/09515089208573056
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References found in this work BETA

The Language of Thought.Jerry A. Fodor - 1975 - Harvard University Press.
Vison.David Marr - 1982 - W. H. Freeman.

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Citations of this work BETA

Distributing Structure Over Time.John E. Hummel & Keith J. Holyoak - 1993 - Behavioral and Brain Sciences 16 (3):464-464.
From Symbols to Neurons: Are We There Yet?Garrison W. Cottrell - 1993 - Behavioral and Brain Sciences 16 (3):454-454.
Making a Middling Mousetrap.Michael R. W. Dawson & Istvan Berkeley - 1993 - Behavioral and Brain Sciences 16 (3):454-455.

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