Knowledge, Concepts, and Categories


The study of mental representation is a central concern in contemporary cognitive psychology. Knowledge, Concepts, and Categories is 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.

Table of Contents

  1. Contributors
  2. Series Preface
  3. Introduction

    Koen Lamberts and David Shanks

  4. 1. Knowledge and Concept Learning

    Evan Heit

  5. 2. Concepts and Similarity

    Ulrike Hahn and Nick Chater

  6. 3. Hierarchical Structure in Concepts and the Basic Level of Categorization

    Gregory L. Murphy and Mary E. Lassaline

  7. 4. Conceptual Combination

    James Hampton

  8. 5. Perceiving and Remembering: Category Stability, Variability and Development

    Linda B. Smith and Larissa K. Samuelson

  9. 6. Distributed Representations and Implicit Knowledge: A Brief Introduction

    David R. Shanks

  10. 7. Declarative and Nondeclarative Knowledge: Insights from Cognitive Neuroscience

    Barbara Knowlton

  11. 8. Implicit Learning and Unconscious Knowledge: Mental Representation, Computational Mechanisms, and Brain Structures

    Thomas Goschke

  12. 9. The Representation of General and Particular Knowledge

    Bruce W. A. Whittlesea

  13. 10. Process Models of Categorization

    Koen Lamberts

  14. 11. Learning Functional Relations Based on Experience with Input-Output Pairs by Humans and Artificial Neural Networks

    Jerome R. Busemeyer, Eunhee Byun, Edward L. Delosh and Mark A. McDaniel

  15. 12. Formal Models for Intra-Categorical Structure that Can Be Used for Data Analysis

    Gert Storms and Paul De Broeck

  16. Index