This Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology.
Dr. Jerome R. Busemeyer is Provost Professor of Psychology at Indiana University.; Dr. Zheng Wang is an Associate Professor at the Ohio State University and directs the Communication and Psychophysiology Lab.; Dr. James T. Townsend is Distinguished Rudy Professor of Psychology at Indiana University.; Dr. Ami Eidels is a senior lecturer in Cognitive Psychology at the School of Psychology, University of Newcastle, Australia.
Preface; 1. Introduction; Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels; Part I. Elementary Cognitive Mechanisms; 2. Multidimensional Signal Detection Theory; F. Gregory Ashby and Fabian A. Soto; 3. Modeling Simple Decisions and Applications Using a Diffusion Model; Roger Ratcliff and Philip Smith; 4. Features of Response Times: Identification of Cognitive Mechanisms through Mathematical Modeling; Daniel Algom, Ami Eidels, Robert X. D. Hawkins, Brett Jefferson, and James T. Townsend; 5. Computational Reinforcement Learning; Todd M. Gureckis and Bradley C. Love; Part II. Basic Cognitive Skills; 6. Why Is Accurately Labeling Simple Magnitudes So Hard? A Past, Present, and Future Look at Simple Perceptual Judgment; Chris Donkin, Babette Rae, Andrew Heathcote, and Scott D. Brown; 7. An Exemplar-Based Random-Walk Model of Categorization and Recognition; Robert M. Nosofsky and Thomas J. Palmeri; 8. Models of Episodic Memory; Amy H. Criss and Marc W. Howard; Part III. Higher Level Cognition; 9. Structure and Flexibility in Bayesian Models of Cognition; Joseph L. Austerweil, Samuel J. Gershman, and Thomas L. Griffiths; 10. Models of Decision Making under Risk and Uncertainty; Timothy J. Pleskac, Adele Diederich, and Thomas S. Wallsten; 11. Models of Semantic Memory; Michael N. Jones, Jon Willits, and Simon Dennis; 12. Shape Perception; Tadamasa Sawada, Yunfeng Li, and Zygmunt Pizlo; Part IV. New Directions; 13. Bayesian Estimation in Hierarchical Models; John K. Kruschke and Wolf Vanpaemel; 14. Model Comparison and the Principle of Parsimony; Joachim Vandekerckhove, Dora Matzke, and Eric-Jan Wagenmakers; 15. Neurocognitive Modeling of Perceptual Decision Making; Thomas J. Palmeri, Jeffrey D. Schall, and Gordon D. Logan; 16. Mathematical and Computational Modeling in Clinical Psychology; Richard W. J. Neufeld; 17. Quantum Models of Cognition and Decision; Jerome R. Busemeyer, Zheng Wang, and Emmanuel Pothos; Index
Show moreThis Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology.
Dr. Jerome R. Busemeyer is Provost Professor of Psychology at Indiana University.; Dr. Zheng Wang is an Associate Professor at the Ohio State University and directs the Communication and Psychophysiology Lab.; Dr. James T. Townsend is Distinguished Rudy Professor of Psychology at Indiana University.; Dr. Ami Eidels is a senior lecturer in Cognitive Psychology at the School of Psychology, University of Newcastle, Australia.
Preface; 1. Introduction; Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels; Part I. Elementary Cognitive Mechanisms; 2. Multidimensional Signal Detection Theory; F. Gregory Ashby and Fabian A. Soto; 3. Modeling Simple Decisions and Applications Using a Diffusion Model; Roger Ratcliff and Philip Smith; 4. Features of Response Times: Identification of Cognitive Mechanisms through Mathematical Modeling; Daniel Algom, Ami Eidels, Robert X. D. Hawkins, Brett Jefferson, and James T. Townsend; 5. Computational Reinforcement Learning; Todd M. Gureckis and Bradley C. Love; Part II. Basic Cognitive Skills; 6. Why Is Accurately Labeling Simple Magnitudes So Hard? A Past, Present, and Future Look at Simple Perceptual Judgment; Chris Donkin, Babette Rae, Andrew Heathcote, and Scott D. Brown; 7. An Exemplar-Based Random-Walk Model of Categorization and Recognition; Robert M. Nosofsky and Thomas J. Palmeri; 8. Models of Episodic Memory; Amy H. Criss and Marc W. Howard; Part III. Higher Level Cognition; 9. Structure and Flexibility in Bayesian Models of Cognition; Joseph L. Austerweil, Samuel J. Gershman, and Thomas L. Griffiths; 10. Models of Decision Making under Risk and Uncertainty; Timothy J. Pleskac, Adele Diederich, and Thomas S. Wallsten; 11. Models of Semantic Memory; Michael N. Jones, Jon Willits, and Simon Dennis; 12. Shape Perception; Tadamasa Sawada, Yunfeng Li, and Zygmunt Pizlo; Part IV. New Directions; 13. Bayesian Estimation in Hierarchical Models; John K. Kruschke and Wolf Vanpaemel; 14. Model Comparison and the Principle of Parsimony; Joachim Vandekerckhove, Dora Matzke, and Eric-Jan Wagenmakers; 15. Neurocognitive Modeling of Perceptual Decision Making; Thomas J. Palmeri, Jeffrey D. Schall, and Gordon D. Logan; 16. Mathematical and Computational Modeling in Clinical Psychology; Richard W. J. Neufeld; 17. Quantum Models of Cognition and Decision; Jerome R. Busemeyer, Zheng Wang, and Emmanuel Pothos; Index
Show morePreface
1. Introduction
Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami
Eidels
Part I. Elementary Cognitive Mechanisms
2. Multidimensional Signal Detection Theory
F. Gregory Ashby and Fabian A. Soto
3. Modeling Simple Decisions and Applications Using a Diffusion
Model
Roger Ratcliff and Philip Smith
4. Features of Response Times: Identification of Cognitive
Mechanisms through Mathematical Modeling
Daniel Algom, Ami Eidels, Robert X. D. Hawkins, Brett Jefferson,
and James T. Townsend
5. Computational Reinforcement Learning
Todd M. Gureckis and Bradley C. Love
Part II. Basic Cognitive Skills
6. Why Is Accurately Labeling Simple Magnitudes So Hard? A Past,
Present, and Future Look at Simple Perceptual Judgment
Chris Donkin, Babette Rae, Andrew Heathcote, and Scott D. Brown
7. An Exemplar-Based Random-Walk Model of Categorization and
Recognition
Robert M. Nosofsky and Thomas J. Palmeri
8. Models of Episodic Memory
Amy H. Criss and Marc W. Howard
Part III. Higher Level Cognition
9. Structure and Flexibility in Bayesian Models of Cognition
Joseph L. Austerweil, Samuel J. Gershman, and Thomas L.
Griffiths
10. Models of Decision Making under Risk and Uncertainty
Timothy J. Pleskac, Adele Diederich, and Thomas S. Wallsten
11. Models of Semantic Memory
Michael N. Jones, Jon Willits, and Simon Dennis
12. Shape Perception
Tadamasa Sawada, Yunfeng Li, and Zygmunt Pizlo
Part IV. New Directions
13. Bayesian Estimation in Hierarchical Models
John K. Kruschke and Wolf Vanpaemel
14. Model Comparison and the Principle of Parsimony
Joachim Vandekerckhove, Dora Matzke, and Eric-Jan Wagenmakers
15. Neurocognitive Modeling of Perceptual Decision Making
Thomas J. Palmeri, Jeffrey D. Schall, and Gordon D. Logan
16. Mathematical and Computational Modeling in Clinical
Psychology
Richard W. J. Neufeld
17. Quantum Models of Cognition and Decision
Jerome R. Busemeyer, Zheng Wang, and Emmanuel Pothos
Index
Dr. Jerome R. Busemeyer is Provost Professor of Psychology at
Indiana University.
Dr. Zheng Wang is an Associate Professor at the Ohio State
University and directs the Communication and Psychophysiology
Lab.
Dr. James T. Townsend is Distinguished Rudy Professor of Psychology
at Indiana University.
Dr. Ami Eidels is a senior lecturer in Cognitive Psychology at the
School of Psychology, University of Newcastle, Australia.
"This excellent book covers important topics, but requires an
extensive background in computational and mathematical psychology
to get the most out of it. " --Gary B Kaniuk, oody's Health
Sciences Book Review
"The liberal, and altogether appropriate, use of figures, graphs,
and tables increases the overall clarity of the expository writing
in all the chapters. These schema headings and graphical organizers
and pictorials lend to the instructional value of the Handbook. The
result is a clear, richly detailed, and imaginative collection of
chapters, each very well written and edited, which describe and
introduce contemporary methodological and statistical
approaches to modeling human cognition. This organizing framework
works well." --PsycCRITIQUES
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