Classification and Cognition

Name: Classification and Cognition
Brand: OUP eBook
Price: 31.49 EUR
Availability: OnlineOnly

William K. Estes(Author)

OUP eBook (Publisher)

1st Edition

Published on 6. January 1994

295 pages

E-Book

PDF with Adobe-DRM

System requirements

978-0-19-536088-2 (ISBN)

€31.49incl. 7% vat

System requirements

for PDF with Adobe-DRM

E-Book Single Licence

Available for download

Description

More details

Other editions

Content

Intro
Contents
1. INTRODUCTION AND BASIC CONCEPTS
1.1 Classification and cognition: an overview
1.1.1 Concepts and categories
1.1.2 Approaches to categorization: two theoretical traditions
1.1.3 Categorization and induction
1.1.4 Remarks on theoretical style
1.2 The array model framework
1.2.1 Representation: attributes, dimensions, and features
1.2.2 The problem of access to memory
1.2.3 Comparison and similarity
1.2.4 The product rule for patterns of binary-valued attributes
1.2.5 The core model for classification
Appendix 1.1 Union and intersection rules for computation of pattern similarity
Appendix 1.2 Attentional learning in the exemplar model
2. CATEGORY STRUCTURES AND CATEGORIZATION
2.1 Similarity in theories of classification
2.1.1 The core model applied to a natural category
2.1.2 From similarity to response probability
2.1.3 An alternative measure of similarity: the contrast model
2.2 Predicting categorization performance
2.2.1 The simplest categorization model in the array framework
2.2.2 On category structures and conceptual levels
3. MODELS FOR CATEGORY LEARNING
3.1 The exemplar-similarity model
3.1.1 Augmentations of the core model
3.1.2 Categorization and identification
3.1.3 Similarity and cognitive distance
3.1.4 Status of the exemplar-similarity model
3.2 Network-based learning models
3.2.1 A simple adaptive network model
3.2.2 The similarity-network model
3.2.3 Pattern to feature transfer
Appendix 3.1 Categorization probability for the exemplar model in relation to initial memory load
Appendix 3.2 Similarity-network output and learning functions for standard four-pattern categorization
Appendix 3.3 Additional details of Experiment 3.1 procedure
4. CATEGORIZATION AND MEMORY PROCESSING
4.1 Concurrent categorizations
4.2 Categorization with constraints on memory
4.2.1 Categorization with constrained repetition lags
4.2.2 Categorization based on short-term memory
4.2.3 Analyses of response frequency data
4.2.4 Analyses of reaction times
4.3 A modular view of exemplar and network models
Appendix 4.1 Method of Experiment 4.1
Appendix 4.2 Learning about invalid cues in concurrent categorizations: Experiment 4.2
Appendix 4.3 Method of Experiment 4.4: categorization in short-term memory
5. ON THE STORAGE AND RETRIEVAL OF CATEGORICAL INFORMATION
5.1 Standard versus observational training procedures
5.1.1 Method for comparison of training procedures
5.1.2 Results for comparisons of training procedures
5.2 Learning on the basis of average or configural prototypes
5.3 Inducing prototypes
5.4 Predicting features from categories
5.4.1 Feature-frequency estimates based on long-term memory
5.4.2 Feature-frequency estimates based on shorter-term memory
5.5 Pattern completion
Appendix 5.1 Induction of prototypes in a correlated-feature category structure: Experiment 5.1
Appendix 5.2 Induction of prototypes in an independent-feature category structure: Experiment 5.2
Appendix 5.3 Method and results of Gluck (1984) study
Appendix 5.4 Derivations of predictions from exemplar and similarity-network models for MacMillan (1987) study
6. EXTENSIONS AND NEW APPLICATIONS OF THE EXEMPLAR-SIMILARITY MODEL
6.1 Processing assumptions
6.2 Extensions and applications
6.2.1 Confusable categories
6.2.2 Transfer between categorizations
6.2.3 The burden of the past: interference in learning successive categorizations or discriminations
6.2.4 Learning multiple categorizations
6.2.5 Category learning in relation to number of categories
6.2.6 Effects of category size
6.2.7 Causal relations
6.2.8 The "dilution effect
6.3 From categorization to recall
6.3.1 Simple cued recall of paired associates
6.3.2 Ordered recall
6.3.3 The crossover effect in sentence memory
6.3.4 Recall without response cueing
6.3.5 A comment on direct recall
6.4 On the extendability of the exemplar-similarity model
Appendix 6.1 Similarity computations for application of the array model to causal inference problems
7. CATEGORIZATION AND RECOGNITION
7.1 Recognition: a window to memory?
7.1.1 Experimental paradigms
7.1.2 Aspects of recognition theory
7.2 Recognition in the array framework
7.2.1 Forced-choice recognition
7.2.2 Old/new recognition
7.2.3 The role of memory load in recognition
7.2.4 Effects of item repetition
7.2.5 Word-frequency and the "mirror effect
7.3 Recognition in the similarity-network model
7.4 Short-term memory search
7.5 On recognition as a measure of memory
Appendix 7.1 Application of signal detectability theory to recognition
Appendix 7.2 Array-model computations for list-length/list-strength design in old/new recognition
Appendix 7.3 Summary of study of memory load in old/new recognition: Experiment 7.1
Appendix 7.4 Summary of repetition study: Experiment 7.2
8. CATEGORIZATION AND COGNITION: REPRISE
8.1 The basis of classification in memory
8.1.1 The new faces of instance memory
8.1.2 Summary of the assumptions of the array-similarity model
8.2 Concepts and categories
8.3 The place of rules in a memory-based theory
8.4 Representation and structure
8.4.1 The issue of independence of attributes
8.4.2 Array versus network representations
8.5 Alternative theoretical approaches
8.5.1 The ACT framework
8.5.2 Hintzman's Minerva model
8.5.3 The general recognition model
8.5.4 Multilayer connectionist networks
8.5.5 On differential tests of models
References
Author Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
R
S
T
U
V
W
Y
Z
Subject Index
A
B
C
D
E
F
G
H
I
L
M
N
O
P
R
S
T
U
W
X

System requirements

Save as PDF Copy link into clipboard

Schweitzer Fachinformationen

Classification and Cognition

Description

More details

Other editions

Additional editions

Content

System requirements