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Preface List of Contributors
Part 1: Introduction
1 An Overview of Computational Cognitive Sciences RON SUN Part II: Cognitive Modeling Paradigms
2 Connectionist Models of Cognition MICHAEL S. C. THOMAS AND JAMES L. MCCLELLAND
3 Bayesian Models of Cognition THOMAS L. GRIFFITHS, CHARLES KEMP, AND JOSHUA B. TENENBAUM
4 Symbolic and Hybrid Models of Cognition TAREK R. BESOLD AND KAI-UWE KÜHNBERGER
5 Logic-Based Modeling of Cognition SELMER BRINGSJORD, MICHAEL GIANCOLA, AND NAVEEN SUNDAR GOVINDARAJULU
6 Dynamical Systems Approaches to Cognition GREGOR SCHÔNER
7 Quantum Models of Cognition JEROME R. BUSEMEYER AND EMMANUEL M. POTHOS
8 Constraints in Cognitive Architectures NIELS TAATGEN AND JOHN ANDERSON
9 Deep Learning MARCO GORI, FRÉDÉRIC PRECIOSO, AND 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 AND YI-WEN WANG
13 Models of Inductive Reasoning BRETT K. HAYES
14 Analogy and Similarity JOHN E. HUMMEL AND LEONIDAS A. A. DOUMAS
15 Mental Models and Algorithms of Deduction PHILIP N. JOHNSON-LAIRD AND SANGEET S. KHEMLANI
16 Computational Models of Decision Making JOSEPH G. JOHNSON AND JEROME R. BUSEMEYER
17 Computational Models of Skill Acquisition STELLAN OHLSSON
18 Computational Models of Episodic Memory PER B. SEDERBERG AND KEVIN P. DARBY
19 Computational Neuroscience Models of Working Memory THOMAS E. HAZY, MICHAEL J. FRANK, AND RANDALL C. O’REILLY
20 Neurocomputational Models of Cognitive Control DEBBIE M. YEE AND TODD S. BRAVER
21 Computational Models of Animal and Human Associative Learning EVAN J. LIVESEY
22 Computational Cognitive Models of Reinforcement Learning KENJI DOYA

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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.