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

This part of the handbook provides an overview of, and a general introduction to, computational cognitive sciences. It discusses the general methodology of computational cognitive modeling and justifies its use in cognitive sciences.

Part 2

The chapters in Part 2 introduce the reader to broadly influential and foundational approaches to computational cognitive sciences. Each of these chapters describes in detail one major approach and provides examples of its use in computational cognitive sciences. 

Part 3

Computational modeling has been applied to a wide range of cognitive functionalities. This part describes modeling of some of the most fundamental and the most important cognitive functionalities. 
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

This part of the handbook addresses computational modeling that researchers have undertaken in many relevant fields. It covers models in fields such as developmental psychology, personality and social psychology, industrial-organizational psychology, psychiatry, psycholinguistics, natural language processing, social simulation, as well as creativity, morality, emotion, and so on.  This part includes some detailed surveys, as well as case studies of projects and models. 

Part 5

This final part explores some significant and consequential issues relevant to computational cognitive sciences and offers some assessments and evaluations. These chapters provide theoretical or historical perspectives on computational cognitive sciences.  

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