The Cambridge Handbook of Computational Psychology

A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.

Ron Sun (Edited by)

9780521674102, Cambridge University Press

Paperback, published 28 April 2008

768 pages
25.4 x 17.8 x 3.4 cm, 1.31 kg

"--With the publication of The Cambridge Handbook of Computational Psychology, the newly emerging, interdisciplinary field of computational cognitive modeling has come of age...a cutting-edge overview of classic and current work in computational psychology. This handbook stakes out this important and promising area of cognitive science...a definitive reference source for the rapidly growing, increasingly important, and strongly interdisciplinary field of computational cognitive modeling...The Cambridge Handbook of Computational Psychology represents a milestone, marking a number of important contributions to the larger field of cognitive science."
--Howard T. Everson, PsycCRITIQUES [May 20, 2009, Vol. 54, Release 20, Article 5]

This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition and various cognitive functionalities through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Given the complexity of the human mind and its manifestation in behavioral flexibility, process-based computational models may be necessary to explicate and elucidate the intricate details of the mind. The key to understanding cognitive processes is often in fine details. Computational models provide algorithmic specificity: detailed, exactly specified, and carefully thought-out steps, arranged in precise yet flexible sequences. These models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many examples.

Part I. Introduction: 1. Introduction to computational cognitive modeling Ron Sun
Part II. Cognitive Modeling Paradigms: 2. Connectionist models of cognition Michael Thomas and James McClelland
3. Bayesian models of cognition Thomas Griffiths, Charles Kemp, and Joshua Tenenbaum
4. Dynamical systems approaches to cognition Gregor Schoener
5. Declarative/ logic-based computational cognitive modeling Selmer Bringsjord
6. Constraints in cognitive architectures Niels Taatgen and John Anderson
Part III. Computational Modeling of Various Cognitive Functionalities and Domains: 7. Computational models of episodic memory Kenneth Norman, Greg Detre, and Sean Polyn
8. Computational models of semantic memory Timothy Rogers
9. Models of categorization John Kruschke
10. Micro-process models of decision making Jerome Busemeyer and Joseph Johnson
11. Models of inductive reasoning Evan Heit
12. Mental logic, mental models, and simulations of human deductive reasoning Philip Johnson-Laird and Yingrui Yang
13. Computational models of skill acquisition Stellan Ohlsson
14. Computational models of implicit learning Axel Cleeremans and Zoltan Dienes
15. Computational models of attention and cognitive control Nicola De Pisapia, Grega Repov and Todd Braver
16. Computational models of developmental psychology Thomas Shultz and Sylvain Sirois
17. Computational models of psycholinguistics Nick Chater and Morten Christiansen
18. Computational models in personality and social psychology Stephen Read and Brian Monroe
19. Cognitive social simulation Ron Sun
20. Models of scientific explanation Paul Thagard and Abninder Litt
21. Cognitive modeling for cognitive engineering Wayne Gray
22. Models of animal learning and their relations to human learning Francisco Lopez and David Shanks
23. Computational modeling of visual information processing Pawan Sinha and Benjamin Balas
24. Models of motor control Ferdinando Mussa-Ivaldi and Sara Solla
Part IV. Concluding Remarks: 25. An evaluation of computational modeling in cognitive science Margaret Boden
26. Putting the pieces together again Aaron Sloman.

Subject Areas: Artificial intelligence [UYQ], Cognition & cognitive psychology [JMR], Computational linguistics [CFX]