Knowledge, Concepts, and Categories

The study of mental representation is a central concern in contemporary cognitive psychology. Knowledge, Concepts, and Categoriesis unusual in that it presents key conclusions from across the different subfields of cognitive psychology. Readers will find data from many areas, including developmental psychology, formal modeling, neuropsychology, connectionism, and philosophy. The difficulty of penetrating the fundamental operations of the mind is reflected in a number of ongoing debates discussed-for example, do distinct brain systems underlie the acquisition and storage of implicit and explicit knowledge, or can the evidence be accommodated by a single-system account of knowledge representation? The book can be divided into three distinct parts. Chapters 1 through 5 offer an introduction to the field; each presents a systematic review of a significant aspect of research on concepts and categories. Chapters 6 through 9 are concerned primarily with issues related to the taxonomy of human knowledge. Finally, Chapters 10 through 12 discuss formal models of categorization and function learning. Contributors: Jerome R. Busemeyer, Eunhee Byun, Nick Chater, Paul De Boeck, Edward L. Delosh, Thomas Goschke, Ulrike Hahn, James Hampton, Evan Heit, Barbara Knowlton, Koen Lamberts, Mary E. Lassaline, Mark A. McDaniel, George L. Murphy, Larissa K. Samuelson, David Shanks, Linda B. Smith, Gert Storms, Bruce W. A. Whittlesea.

Contributors
Series Preface
Introduction
Knowledge and concept learning
Theoretical arguments
Experimental evidence for specific influences of
knowlegde
Influences of more general knowledge
Implications for categorization models
Relations to inductive reasoning
Relations to memory
Conclusion
References
Note
Concepts and similarity
Concepts and similarity: The chicken and the egg?
Concepts
Similarity
Concepts and similarity
Conclusion
References
Notes
Hierarchical structure in concepts and the basic level of categorization
Hierarchical structure of categories
The basic level of categorization
The other levels
The basic level in non-object domains
Expertise
Conclusion
References
Notes
Conceptual combination
Types of conceptual combination
Intersective combination
Modifier-head combination
Conclusions
References
Notes
Perceiving and remembering: Category stability, variability and development
Theories about concepts
Perceiving and remembering
Learning names for things
What about concepts?
References
Distributed representations and implicit knowledge: A brief introduction
Connectionism and knowledge representation
Structured representations
Implicit and explicit knowledge
Conclusion
References
Note
Declarative and nondeclarative knowledge: Insights from cognitive neuroscience
Introduction
The relationship between knowledge and memory
Declarative and nondeclarative knowledge
Declarative knowledge and amnesia
Nondeclarative skill learning
Dissociations in skill learning
Priming
Priming and brain imaging
Conceptual priming
Priming and recognition
Sequence Learning
Category-level knowledge
Artificial grammar learning
Fuzzy categories
Exemplar-based models
Amnesia as a storage deficit
Consolidation
Functional imaging of hippocampus
Electrophysiological data
Conclusion
References
Implicit learning and unconscious knowledge: Mental representation, computational mechanisms, and brain structures
Introduction: Phenomena, tasks, and questions
Dissociations and operational criteria
Question 1: Does implicit learning lead to unconscious
knowledge?
Question 2: Does implicit learning require attention or is it automatic?
Question 3: Does implicit learning lead to abstract knowledge?
Question 4: What are the computational mechanisms
underlying implicit learning?
Question 5: Does implicit learning involve specific brain structures?
Conclusions
References
Notes
The representation of general and particular knowledge
Conclusions
References
Notes
Process models of categorization
A framework for perceptual categorization
Principles of formal modelling
Perceptual processing in categorization
Memory access and decision making
Another model of response times in categorization
Conclusion
References
Note
Learning functional relations based on experience with input-output pairs by humans and artificial neural networks
Decisions, predicitions, and abstract concepts
Category versus function learning paradigm
Summary of basic findings on single-cue function learning
Cognitive models of function learning
Reproducing the basic findings of function-learning research
Conclusions
References
Formal models for intra-categorical structure that can be used for data analysis
Entity by property matrices
Intra-categorical structure in the major theoretical views on concepts . . .
Conclusions
References
Notes
Index
Table of Contents provided by Publisher. All Rights Reserved.

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Knowledge, Concepts, and Categories

Summary

Table of Contents

Supplemental Materials