Perspectives in Neural Computing

Proceedings of the Sixth Neural Computation and Psychology Workshop, Li¨ge, Belgium, 16-18 September 2000

By: Robert M. French (Editor), Jacques P. Sougne (Editor)

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Paperback | 23 March 2001

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340 Pages

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Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena.
With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections:
The neural basis of cognition
Development and category learning
Implicit learning
Social cognition Evolution
Semantics
Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.

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Applying Neuroanatomical Distinctions to Connectionist Cognitive Modelling	p. 3
Pseudopatterns and Dual-Network Memory Models: Advantages and Shortcomings	p. 13
A Learning Algorithm for Synfire Chains	p. 23
Towards a Spatio-Temporal Analysis Tool for fMRI Data: An Application to Depth-from-Motion Processing in Humans	p. 33
A Simple Model Exhibiting Scalar Timing	p. 43
Modularity and Specialized Learning in the Organization of Behaviour	p. 53
Modeling Modulatory Aspects in Association Processes	p. 63
Recognition of Novelty Made Easy: Constraints of Channel Capacity on Generative Networks	p. 73
A Biologically Plausible Maturation of an ART Network	p. 83
Developing Knowledge about Living Things: A Connectionist Investigation	p. 95
Paying Attention to Relevant Dimensions: A Localist Approach	p. 105
Coordinating Multiple Sensory Modalities While Learning to Reach	p. 113
Modelling Cognitive Development with Constructivist Neural Networks	p. 123
Learning Action Affordances and Action Schemas	p. 133
A Three-Layer Configural Cue Model of Category Learning Rates	p. 143
A Revival of Turing's Forgotten Connectionist Ideas: Exploring Unorganized Machines	p. 153
Visual Crowding and Category-Specific Deficits: A Neural Network Model	p. 163
Implicit Learning of Regularities in Western Tonal Music by Self-Organization	p. 175
Rules vs. Statistics in Implicit Learning of Biconditional Grammars	p. 185
Hidden Markov Model Interpretations of Neural Networks	p. 197
A Connectionist Model of Person Perception and Stereotype Formation	p. 209
Learning about an Absent Cause: Discounting and Augmentation of Positively and Independently Related Causes	p. 219
Exploring the Baldwin Effect in Evolving Adaptable Control Systems	p. 231
Borrowing Dynamics from Evolution: Association using Catalytic Network Models	p. 243
Evolving Modular Architectures for Neural Networks	p. 253
Evolution, Development and Learning - A Nested Hierarchy?	p. 263
Learning Lexical Properties from Word Usage Patterns: Which Context Words Should be Used?	p. 273
Associative Computation and Associative Prediction	p. 283
The Development of Small-World Semantic Networks	p. 293
What is the Dimensionality of Human Semantic Space?	p. 303
Author Index	p. 313
Subject Index	p. 315
Table of Contents provided by Blackwell. All Rights Reserved.

Perspectives in Neural Computing

Proceedings of the Sixth Neural Computation and Psychology Workshop, Li¨ge, Belgium, 16-18 September 2000

At a Glance

Paperback

Shipping

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