The Oxford Handbook of Computational and Mathematical Psychology

Hardcover | May 1, 2015

byJerome R. Busemeyer, Zheng Wang, James T. Townsend

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This Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology. With chapters written by leading scientists across a variety of subdisciplines, it examines the field's influence on related research areas such ascognitive psychology, developmental psychology, clinical psychology, and neuroscience. The Handbook emphasizes examples and applications of the latest research, and will appeal to readers possessing various levels of modeling experience.The Oxford Handbook of Computational and mathematical Psychology covers the key developments in elementary cognitive mechanisms (signal detection, information processing, reinforcement learning), basic cognitive skills (perceptual judgment, categorization, episodic memory), higher-level cognition(Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (Bayesian estimation and other new model comparison methods), and emerging new directions in computation and mathematical psychology (neurocognitive modeling, applications to clinical psychology, quantumcognition). The Handbook would make an ideal graduate-level textbook for courses in computational and mathematical psychology. Readers ranging from advanced undergraduates to experienced faculty members and researchers in virtually any area of psychology - including cognitive science and related social andbehavioral sciences such as consumer behavior and communication - will find the text useful.

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This Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology. With chapters written by leading scientists across a variety of subdisciplines, it examines the field's influence on related research areas such ascognitive psychology, developmental psychology, c...

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...

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Format:HardcoverDimensions:424 pages, 10.12 × 7.2 × 1.42 inPublished:May 1, 2015Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199957991

ISBN - 13:9780199957996

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Table of Contents

Preface1. Jerome R. Busemeyer, Zheng Wang, James T. Townsend, and Ami Eidels: IntroductionPart I. Elementary Cognitive Mechanisms2. F. Gregory Ashby and Fabian A. Soto: Multidimensional Signal Detection Theory3. Roger Ratcliff and Philip Smith: Modeling Simple Decisions and Applications Using a Diffusion Model4. Daniel Algom, Ami Eidels, Robert X. D. Hawkins, Brett Jefferson, and James T. Townsend: Features of Response Times: Identification of Cognitive Mechanisms through Mathematical Modeling5. Todd M. Gureckis and Bradley C. Love: Computational Reinforcement LearningPart II. Basic Cognitive Skills6. Chris Donkin, Babette Rae, Andrew Heathcote, and Scott D. Brown: Why Is Accurately Labeling Simple Magnitudes So Hard? A Past, Present, and Future Look at Simple Perceptual Judgment7. Robert M. Nosofsky and Thomas J. Palmeri: An Exemplar-Based Random-Walk Model of Categorization and Recognition8. Amy H. Criss and Marc W. Howard: Models of Episodic MemoryPart III. Higher Level Cognition9. Joseph L. Austerweil, Samuel J. Gershman, and Thomas L. Griffiths: Structure and Flexibility in Bayesian Models of Cognition10. Timothy J. Pleskac, Adele Diederich, and Thomas S. Wallsten: Models of Decision Making under Risk and Uncertainty11. Michael N. Jones, Jon Willits, and Simon Dennis: Models of Semantic Memory12. Tadamasa Sawada, Yunfeng Li, and Zygmunt Pizlo: Shape PerceptionPart IV. New Directions13. John K. Kruschke and Wolf Vanpaemel: Bayesian Estimation in Hierarchical Models14. Joachim Vandekerckhove, Dora Matzke, and Eric-Jan Wagenmakers: Model Comparison and the Principle of Parsimony15. Thomas J. Palmeri, Jeffrey D. Schall, and Gordon D. Logan: Neurocognitive Modeling of Perceptual Decision Making16. Richard W. J. Neufeld: Mathematical and Computational Modeling in Clinical Psychology17. Jerome R. Busemeyer, Zheng Wang, and Emmanuel Pothos: Quantum Models of Cognition and DecisionIndex