Semantic Cognition: A Parallel Distributed Processing Approach

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MIT Press, 2004 - 425 páginas
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This groundbreaking monograph offers a mechanistic theory of the representation and use of semantic knowledge, integrating the strengths and overcoming many of the weaknesses of hierarchical, categorization-based approaches, similarity-based approaches, and the approach often called "theory theory." Building on earlier models by Geoffrey Hinton in the 1980s and David Rumelhart in the early 1990s, the authors propose that performance in semantic tasks arises through the propagation of graded signals in a system of interconnected processing units. The representations used in performing these tasks are patterns of activation across units, governed by weighted connections among them. Semantic knowledge is acquired through the gradual adjustment of the strengths of these connections in the course of day-to-day experience.

The authors show how a simple computational model proposed by Rumelhart exhibits a progressive differentiation of conceptual knowledge, paralleling aspects of cognitive development seen in the work of Frank Keil and Jean Mandler. The authors extend the model to address aspects of conceptual knowledge acquisition in infancy, disintegration of conceptual knowledge in dementia, "basic-level" effects and their interaction with expertise, and many findings introduced to support the idea that semantic cognition is guided by naive, domain-specific theories.
  

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Índice

Categories Hierarchies and Theories
1
CategorizationBased Models
3
The TheoryTheory
28
Toward a Mechanistic Model of Semantic Knowledge
42
Summary
46
A POP Theory of Semantic Cognition
49
The Rumelhart FeedForward Network
55
Interpretation and Storage of New Information
63
Category Coherence
231
Category Coherence
236
Category Coherence
240
Illusory Correlations
250
CategoryDependent Attribute Weighting
258
Summary of Findings
263
Inductive Projection and Conceptual Reorganization
265
Inductive Projection
269

Inferences Based on New Semantic Information
66
Discussion of the Rumelhart Network
69
Latent Hierarchies in Distributed Representations
83
Progressive Differentiation of Concept Representations
84
Simulating Loss of Differentiation in Dementia
104
Summary of Basic Simulations
113
Extended Training Corpus for Use in Subsequent Simulations
114
Emergence of Category Structure in Infancy
121
A Brief Overview of the Literature
123
Simulating Preverbal Conceptual Development in the Rumelhart Model
138
Capturing Conceptual Differentiation in Infancy
144
Discussion
168
Naming Things Privileged Categories Familiarity Typicality and Expertise
175
A PDF Account of BasicLevel Effects
182
Learning with Basic Names Most Frequent
189
Learning with All Names Equally Frequent
197
Effects of the Attribute Structure of the Training Corpus
204
Conclusions from Simulations 5153
209
Familiarity and Expertise Effects
212
DomainSpecific Expertise
219
Different Kinds of Expertise in the Same Domain
225
Generality of the Observed Simulation Results
229
Inductive Projection and Its Differentiation in Development
270
Differential Projection of Different Kinds of Properties
276
Reorganization and Coalescence
282
Coalescence
283
Discussion
292
The Role of Causal Knowledge in Semantic Task Performance
297
The Role of Causal Properties of Objects in Semantic Cognition
302
Toward a POP Account of Causal Knowledge and Causal Inference
309
The Basis of Explanations
327
Comparison of the PDP Approach with TheoryBased Approaches
338
Core Principles General Issues and Future Directions
347
Perspectives on General Issues in the Study of Cognition
367
Semantic Cognition in the Brain
376
Conclusion
380
Simulation Details
381
Training Patterns
393
Individuating Specific Items in the Input
399
Notes
403
References
407
Index
423
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Representation Reconsidered
William M. Ramsey
Vista previa restringida - 2007
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Sobre el autor (2004)

Timothy T. Rogers is a research scientist at the Medical Research Council Cognition and Brain Sciences Unit in Cambridge, England.

Información bibliográfica