The Cambridge Handbook of Computational Cognitive Sciences
Ron Sun (Ed.)
RPI, Troy, NY, USA
Published by Cambridge University Press, Cambridge, UK
Description of the Handbook
The Cambridge Handbook of Computational Cognitive Sciences (CHCCS) is part of the Cambridge Handbook in Psychology series. CHCCS is a definitive reference source for the increasingly important and interdisciplinary field of computational cognitive modeling in the cognitive sciences.
Research in computational cognitive sciences explores the essence of cognition (broadly construed) and various cognitive functionalities through developing detailed, mechanistic, process-based understanding by specifying corresponding computational mechanisms and processes.
CHCCS appeals to advanced students and researchers of this research community, as well as to advanced students and researchers in the cognitive sciences in general, including in philosophy, in cognitive psychology, in social psychology, in linguistics, in anthropology, in neuroscience, and so on. For example, it could serve well as a textbook for courses in cognitive and behavioral sciences programs. CHCCS could also be used by social science researchers, intelligent systems engineers, psychology or education software developers, and so on.
Part 1
Part 2
Part 3
This part surveys and explores cognitive modeling research, in terms of computational mechanisms and processes, of categorization, memory, reasoning, decision making, learning, and so on. It describes some of the most prominent models in the field. These computational models constitute significant advances in cognitive sciences and shed light on corresponding empirical phenomena and data.
Part 4
Part 5
Detailed Table of Contents
The Cambridge Handbook of Computational Cognitive Sciences
Volume 1:
Table of Contents
Preface
List of Contributors
Part 1: Introduction
Chapter 1. An Overview of Computational Cognitive Sciences
Ron Sun
Part 2: Cognitive Modeling Paradigms
Chapter 2. Connectionist Models of Cognition
Michael S. C. Thomas, James L. McClelland
Chapter 3. Bayesian Models of Cognition
Thomas L. Griffiths, Charles Kemp, Joshua B. Tenenbaum
Chapter 4. Symbolic and Hybrid Models of Cognition
Tarek R. Besold, Kai-Uwe Kühnberger
Chapter 5. Logic-Based Modeling of Cognition
Selmer Bringsjord, Michael Giancola, Naveen Sundar Govindarajulu
Chapter 6. Dynamical Systems Approaches to Cognition
Gregor Schöner
Chapter 7. Quantum Models of Cognition
Jerome R. Busemeyer, Emmanuel M. Pothos
Chapter 8. Constraints in Cognitive Architectures
Niels Taatgen, John Anderson
Chapter 9. Deep Learning
Marco Gori, Frédéric Precioso, Edmondo Trentin
Chapter 10. Reinforcement Learning
Kenji Doya
Part 3: Computational Modeling of Basic Cognitive Functionalities
Chapter 11. Computational Models of Categorization
Kenneth J. Kurtz
Chapter 12. Computational Cognitive Neuroscience Models of Categorization
F. Gregory Ashby, Yi-Wen Wang
Chapter 13. Models of Inductive Reasoning
Brett K. Hayes
Chapter 14. Analogy and Similarity
John E. Hummel, Leonidas A. A. Doumas
Chapter 15. Mental Models and Algorithms of Deduction
Philip N. Johnson-Laird, Sangeet S. Khemlani
Chapter 16. Computational Models of Decision Making
Joseph G. Johnson, Jerome R. Busemeyer
Chapter 17. Computational Models of Skill Acquisition
Stellan Ohlsson
Chapter 18. Computational Models of Episodic Memory
Per B. Sederberg, Kevin P. Darby
Chapter 19. Computational Neuroscience Models of Working Memory
Thomas E. Hazy, Michael J. Frank, Randall C. O’Reilly
Chapter 20. Neurocomputational Models of Cognitive Control
Debbie M. Yee, Todd S. Braver
Chapter 21. Computational Models of Animal and Human Associative Learning
Evan J. Livesey
Chapter 22. Computational Cognitive Models of Reinforcement Learning
Kenji Doya
Volume 2:
Table of Contents
Part 4: Computational Modeling in Various Cognitive Fields
Chapter 23. Computational Models of Developmental Psychology
Thomas R. Shultz, Ardavan S. Nobandegani
Chapter 24. Computational Models in Personality and Social Psychology
Stephen J. Read, Brian Monroe
Chapter 25. Computational Modeling in Industrial-Organizational Psychology
Jeffrey B. Vancouver
Chapter 26. Computational Modeling in Psychiatry
Cody J. Walters, Sophia Vinogradov, A. David Redish
Chapter 27. Computational Psycholinguistics
Matthew W. Crocker, Harm Brouwer
Chapter 28. Natural Language Understanding and Generation
Marjorie McShane, Sergei Nirenburg
Chapter 29. Computational Models of Creativity
Sébastien Hélie, Ana-Maria Olteteanu
Chapter 30. Computational Models of Emotion and Cognition-Emotion Interaction
Eva Hudlicka
Chapter 31. Computational Approaches to Morality
Paul Bello, Bertram F. Malle
Chapter 32. Cognitive Modeling in Social Simulation
Ron Sun
Chapter 33. Cognitive Modeling for Cognitive Engineering
Matthew L. Bolton, Wayne D. Gray
Chapter 34. Modeling Vision
Lukas Vogelsang, Pawan Sinha
Chapter 35. Models of Multi-Level Motor Control
Martin Giese, David Ungarish, Tamar Flash
Part 5: General Discussion
Chapter 36. Model Validation, Comparison, and Selection
Leslie M. Blaha, Kevin A. Gluck
Chapter 37. Philosophical Issues in Computational Cognitive Sciences
Mark Sprevak
Chapter 38. Evaluation of Computational Modeling in Cognitive Sciences
Margaret A. Boden
Ordering the Book
https://www.amazon.com/Cambridge-Computational-Cognitive-Handbooks-Psychology/dp/1108485073
Questions Regarding the book
dr.ron.sun AT gmail.com