Formal Approaches in Categorization

Cambridge University Press, 1/27/2011
EAN 9780521140720, ISBN10: 0521140722

Paperback, 348 pages, 22.8 x 15.2 x 2 cm
Language: English

The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come.

1. Introduction Emmanuel M. Pothos and Andy J. Wills
2. The generalized context model
an exemplar model of classification Robert M. Nosofsky
3. Prototype models of categorization
basic formulation, predictions, and limitations John Paul Minda and J. David Smith
4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox
5. Semantics without categorization Timothy T. Rogers and James L. McClelland
6. Models of attentional learning John K. Kruschke
7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren
8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum
9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines
10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis
11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley
12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder
13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy
14. Formal models of categorization
insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza
15. Comments on models and categorization theories
the razor's edge Douglas Medin.

Advance praise: 'A great introductory volume for advanced undergraduates, beginning graduate students, or those new to categorization research. This is the first place to turn before reading the original research papers, with chapters written by the same people who conducted that original research. The volume also provides an important object lesson on how formal approaches can critically shape our understanding of human cognition and is required reading for anyone interested in categorization.' Thomas Palmeri, Psychological Sciences, Vanderbilt University