Parallel Distributed Processing, Volume 2: Explorations in the Microstructure of Cognition: Psychological and Biological Models / Edition 1

by James L. Mcclelland, David E. Rumelhart, PDP Research Group

Overview

What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind.

The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network.

Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought.

Product Details

ISBN-13:	9780262631105
Publisher:	MIT Press
Publication date:	07/29/1987
Series:	Bradford Books Series , #2
Edition description:	Reprint
Pages:	632
Product dimensions:	6.00(w) x 9.00(h) x 1.30(d)
Age Range:	18 Years

About the Author

James L. McClelland is Professor of Psychology and Director of the Center for Mind, Brain, and Computation at Stanford University. He is the coauthor of Parallel Distributed Processing (1986) and Semantic Cognition (2004), both published by the MIT Press. With David E. Rumelhart, he was awarded the 2002 University of Louisville Grawemeyer Award for Psychology for his work in the field of cognitive neuroscience on a cognitive framework called parallel distributed processing and the concept of connectionism.

David E. Rumelhart (1942-2011) served as Professor of Psychology at the University of California, San Diego and Stanford University. With James McClelland, he was awarded the 2002 University of Louisville Grawemeyer Award for Psychology for his work in the field of cognitive neuroscience on a cognitive framework called parallel distributed processing and the concept of connectionism.

Table of Contents

Preface to Volume 2
Addresses of the PDP Research Group
IV PSYCHOLOGICAL PROCESSES
14 Schemata and Sequential Thought Processes in PDP Models
D.E. Rumelhart, P. Smolensky, J.L. McClelland, and G.E. Hinton
15 Interactive Processes in Speech Perception: The TRACE
Model
J.L. McClelland and J.L. Elman
16 The Programmable Blackboard Model of Reading
J.L. McClelland
17 A Distributed Model of Human Learning and Memory
J.L. McClelland and D.E. Rumelhart
18 On Learning the Past Tenses of English Verbs
D.E. Rumelhart and J.L. McClelland
19 Mechanisms of Sentence Processing: Assigning Roles to
Constituents
J.L. McClelland and A.H. Kawamoto
V BIOLOGICAL MECHANISMS
20 Certain Aspects of the Anatomy and Physiology of the
Cerbral CorteX
F.H.C. Crick and C. Asanuma
21 Open Questions About Computation in Cerebral CorteX
T.J. Sejnowski
22 Neural and Conceptual Interpretation of PDP Models
P. Smolensky
23 Biologically Plausible Models of Place Recognition
and Goal Location
D. Zipser
24 StateDependent Factors Influencing Neural
Plasticity: A Partial Account of the Critical Period
P.W. Munro
25 Amnesia and Distributed Memory
J.L. McClelland and D.E. Rumelhart
VI CONCLUSION
26 Reflections on Cognition and Parallel Distributed Processing
D.A. Norman
Future Directions
References
IndeX

What People are Saying About This

From the Publisher

"Rumelhart and McClelland propose that what is stored in memory is not specific facts or events, but rather the relationships between the various aspects of those facts or events as they are encoded in groupings of neuronal cells or patterns of cell activity." Daniel Coleman, The NewYork Times

Artificial Intelligence Special Interest Group Newsletter

[This is] a comprehensive compilation of neural network research and development.
There are algorithms you can use to explore various methods in the field. If you want information on neural network technology in book form, this is the set to own.

The New York Times - Daniel Coleman

Rumelhart and McClelland propose that what is stored in memory is not specific facts or events, but rather the relationships between the various aspects of those facts or events as they are encoded in groupings of neuronal cells or patterns of cell activity.

Editorial Reviews

The most intense, most effective and most mind-stretching view of neurocomputing origins, theories and concerns to yet reach print.—Intelligence—

From the Publisher

The most intense, most effective and most mind-stretching view of neurocomputing origins, theories and concerns to yet reach print.

Intelligence