The Cambridge Handbook of Computational Cognitive Sciences

A summary and comprehensive reference of the field of computational cognitive sciences covering methods, paradigms, and models.

Ron Sun (Edited by)

9781108485074, Cambridge University Press

Multiple-component retail product, published 11 May 2023

900 pages
25.9 x 18.4 x 7.5 cm, 2.7 kg

'Computational models have been central to cognitive science since the 1950s, making important contributions to the design and testing of theoretical explanations of mind. Through chapters by an army of leading experts, this Handbook provides a remarkably broad overview of computational modeling. Researchers and students in cognitive science will find it indispensable.' Paul Thagard, University of Waterloo, Canada

The Cambridge Handbook of Computational Cognitive Sciences is a comprehensive reference for this rapidly developing and highly interdisciplinary field. Written with both newcomers and experts in mind, it provides an accessible introduction of paradigms, methodologies, approaches, and models, with ample detail and illustrated by examples. It should appeal to researchers and students working within the computational cognitive sciences, as well as those working in adjacent fields including philosophy, psychology, linguistics, anthropology, education, neuroscience, artificial intelligence, computer science, and more.

Volume 1: Part I. Introduction: 1. An overview of computational cognitive sciences Ron Sun
Part II. Cognitive modeling paradigms: 2. Connectionist models of cognition Michael S. C. Thomas, James L. McClelland
3. Bayesian models of cognition Thomas L. Griffiths, Charles Kemp, Joshua B. Tenenbaum
4. Symbolic and hybrid models of cognition Tarek R. Besold, Kai-Uwe Kühnberger
5. Logic-Based modeling of cognition Selmer Bringsjord, Michael Giancola, Naveen Sundar Govindarajulu
6. Dynamical systems approaches to cognition Gregor Schöner
7. Quantum models of cognition Jerome R. Busemeyer, Emmanuel M. Pothos
8. Constraints in cognitive architectures Niels Taatgen, John Anderson
9. Deep learning Marco Gori, Frédéric Precioso, Edmondo Trentin
10. Reinforcement learning Kenji Doya
Part III. Computational modeling of basic cognitive functionalities: 11. Computational models of categorization Kenneth J. Kurtz
12. Computational cognitive neuroscience models of categorization F. Gregory Ashby, Yi-Wen Wang
13. Models of inductive reasoning Brett K. Hayes
14. Analogy and similarity John E. Hummel, Leonidas A. A. Doumas
15. Mental models and the algorithms of deduction Philip N. Johnson-Laird, Sangeet S. Khemlani
16. Computational models of decision making Joseph G. Johnson, Jerome R. Busemeyer
17. Computational models of skill acquisition Stellan Ohlsson
18. Computational models of episodic memory Per B. Sederberg, Kevin P. Darby
19. Computational neuroscientific models of working memory Thomas E. Hazy, Michael J. Frank, Randall C. O'Reilly
20. Neurocomputational models of cognitive control Debbie M. Yee, Todd S. Braver
21. Computational models of animal and human associative learning Evan J. Livesey
22. Computational and cognitive models of reinforcement learning Kenji Doya
Volume 2: Part IV. Computational modeling in various cognitive fields: 23. Computational models of developmental psychology Thomas R. Shultz, Ardavan S. Nobandegani
24. Computational models in personality and social psychology Stephen J. Read, Brian Monroe
25. Computational modeling in industrial-organizational psychology Jeffrey B. Vancouver
26. Computational modeling in psychiatry Cody J. Walters, Sophia Vinogradov, A. David Redish
27. Computational psycholinguistics Matthew W. Crocker, Harm Brouwer
28. Natural language understanding and generation Marjorie McShane, Sergei Nirenburg
29. Computational models of creativity Sébastien Hélie, Ana-Maria Olteteanu
30. Computational models of emotion and cognition-emotion interaction Eva Hudlicka
31. Computational approaches to morality Paul Bello, Bertram F. Malle
32. Cognitive modeling in social simulation Ron Sun
33. Cognitive modeling for cognitive engineering Matthew L. Bolton, Wayne D. Gray
34. Modeling vision Lukas Vogelsang, Pawan Sinha
35. Models of multi-level motor control Martin Giese, David Ungarish, Tamar Flash
Part V. General discussion: 36. Model validation, comparison and selection Leslie M. Blaha, Kevin A. Gluck
37. Philosophical issues in computational cognitive sciences Mark Sprevak
38. An evaluation of computational modeling in cognitive sciences Margaret A. Boden.

Subject Areas: Cognitivism, cognitive theory [JMAQ]