Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition

Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two‐volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called “deep networks”—systems that build on key ideas presented in the PDP volumes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cognitive Science - A Multidisciplinary Journal Wiley

Parallel Distributed Processing at 25: Further Explorations in the Microstructure of Cognition

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Publisher
Wiley
Copyright
"Copyright © 2014, Cognitive Science Society, Inc."
ISSN
0364-0213
eISSN
1551-6709
DOI
10.1111/cogs.12148
pmid
25087578
Publisher site
See Article on Publisher Site

Abstract

This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two‐volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called “deep networks”—systems that build on key ideas presented in the PDP volumes.

Journal

Cognitive Science - A Multidisciplinary JournalWiley

Published: Aug 1, 2014

Keywords: ; ; ; ; ; ; ;

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