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Connectionist Models of Learning, Development and Evolution

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Cover of 'Connectionist Models of Learning, Development and Evolution'

Table of Contents

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    Book Overview
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    Chapter 1 Applying Neuroanatomical Distinctions to Connectionist Cognitive Modelling
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    Chapter 2 Pseudopatterns and dual-network memory models: Advantages and shortcomings
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    Chapter 3 A Learning Algorithm for Synfire Chains
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    Chapter 4 Towards a Spatio-Temporal Analysis Tool for fMRI Data: An Application to Depth-from-Motion Processing in Humans
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    Chapter 5 A Simple Model Exhibiting Scalar Timing
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    Chapter 6 Modularity and Specialized Learning in the Organization of Behaviour
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    Chapter 7 Modeling Modulatory Aspects in Association Processes
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    Chapter 8 Recognition of Novelty Made Easy: Constraints of Channel Capacity on Generative Networks
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    Chapter 9 A Biologically Plausible Maturation of an ART Network
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    Chapter 10 Developing Knowledge about Living Things: A Connectionist Investigation
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    Chapter 11 Paying Attention to Relevant Dimensions: A Localist Approach
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    Chapter 12 Coordinating Multiple Sensory Modalities While Learning to Reach
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    Chapter 13 Modelling Cognitive Development with Constructivist Neural Networks
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    Chapter 14 Learning Action Affordances and Action Schemas
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    Chapter 15 A Three-Layer Configural Cue Model of Category Learning Rates
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    Chapter 16 A Revival of Turing’s Forgotten Connectionist Ideas: Exploring Unorganized Machines
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    Chapter 17 Visual Crowding and Category-Specific Deficits: a Neural Network Model
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    Chapter 18 Implicit Learning of Regularities in Western Tonal Music by Self-Organization
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    Chapter 19 Rules vs. Statistics in Implicit Learning of Biconditional Grammars
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    Chapter 20 Hidden Markov Model Interpretations of Neural Networks
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    Chapter 21 A Connectionist Model of Person Perception and Stereotype Formation
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    Chapter 22 Learning about an Absent Cause: Discounting and Augmentation of Positively and Independently Related Causes
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    Chapter 23 Exploring the Baldwin Effect in Evolving Adaptable Control Systems
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    Chapter 24 Borrowing Dynamics from Evolution: Association using Catalytic Network Models
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    Chapter 25 Evolving Modular Architectures for Neural Networks
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    Chapter 26 Evolution, Development and Learning — a Nested Hierarchy?
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    Chapter 27 Learning Lexical Properties from Word Usage Patterns: Which Context Words Should be Used?
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    Chapter 28 Associative Computation and Associative Prediction
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    Chapter 29 The Development of Small-world Semantic Networks
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    Chapter 30 What is the Dimensionality of Human Semantic Space?
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Connectionist Models of Learning, Development and Evolution
Published by
Springer, London, January 2001
DOI 10.1007/978-1-4471-0281-6
978-1-85233-354-6, 978-1-4471-0281-6

Robert M. French, Jacques P. Sougné

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 67%
Student > Ph. D. Student 1 33%
Readers by discipline Count As %
Engineering 2 67%
Computer Science 1 33%