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Classification and Cognition.
Based on the Fitts Lectures, this volume presents a core set of concepts and principles that proposes a unified interpretation of a wide variety of phenomena of memory, categorization and decision-making. These theories are then applied to issues in category-learning and recognition.
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cary :
Oxford University Press, Incorporated,
1994.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- ""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""