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The Cambridge Handbook of Computational Psychology

$78.00 (Z)

textbook

Part of Cambridge Handbooks in Psychology

Ron Sun, Michael Thomas, James McClelland, Thomas Griffiths, Charles Kemp, Joshua Tenenbaum, Gregor Schoener, Selmer Bringsjord, Niels Taatgen, John Anderson, Kenneth Norman, Greg Detre, Sean Polyn, Timothy Rogers, John Kruschke, Jerome Busemeyer, Joseph Johnson, Evan Heit, Philip Johnson-Laird, Yingrui Yang, Axel Cleeremans, Zoltan Dienes, Nicola De Pisapia, Grega Repovs, Todd Braver, Thomas Shultz, Sylvain Sirois, Nick Chater, Morten Christiansen, Stephen Read, Brian Monroe, Paul Thagard, Abninder Litt, Wayne Gray, Francisco Lopez, David Shanks, Pawan Sinha, Benjamin Balas, Ferdinando Mussa-Ivaldi, Sara Solla, Aaron Sloman
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  • Date Published: April 2008
  • availability: In stock
  • format: Paperback
  • isbn: 9780521674102

$78.00 (Z)
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About the Authors
  • This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Computational models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many examples.

    • Combines breadth of coverage with definitive statements by leading scientists in this field
    • Computational models provide both conceptual clarity and precision at the same time
    • Provides experts with quick overviews while also being an entry point into the field for the next generation of researchers
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    Reviews & endorsements

    "[...] This edited volume by Sun (Rensselaer Polytechnic Institute) comprises two sections:[...] The first section will attract broader interest, especially from students, because of its juxtaposition of distinct approaches including connectionist, Bayesian, and logical modeling. The second section covers a range of topics, from memory and learning to decision making and cognitive control. [...] Given that the application chapters are largely independent of the methodological chapters, a dedicated instructor could cover more extensive ground by selecting primary papers on a desired topic. However, researchers who use computational approaches, or who want to become better consumers of computational psychology literature, may find this to be a valuable compilation of major ideas in this area. Recommended.
    --S.A. Huettel, Duke University CHOICE

    "--With the publication of The Cambridge Handbook of Computational Psychology, the newly emerging, interdisciplinary field of computational cognitive modeling has come of age...a cutting-edge overview of classic and current work in computational psychology. This handbook stakes out this important and promising area of cognitive science...a definitive reference source for the rapidly growing, increasingly important, and strongly interdisciplinary field of computational cognitive modeling...The Cambridge Handbook of Computational Psychology represents a milestone, marking a number of important contributions to the larger field of cognitive science."
    --Howard T. Everson, PsycCRITIQUES [May 20, 2009, Vol. 54, Release 20, Article 5]

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    Product details

    • Date Published: April 2008
    • format: Paperback
    • isbn: 9780521674102
    • length: 768 pages
    • dimensions: 254 x 178 x 34 mm
    • weight: 1.31kg
    • availability: In stock
  • Table of Contents

    Part I. Introduction:
    1. Introduction to computational cognitive modeling Ron Sun
    Part II. Cognitive Modeling Paradigms:
    2. Connectionist models of cognition Michael Thomas and James McClelland
    3. Bayesian models of cognition Thomas Griffiths, Charles Kemp, and Joshua Tenenbaum
    4. Dynamical systems approaches to cognition Gregor Schoener
    5. Declarative/ logic-based computational cognitive modeling Selmer Bringsjord
    6. Constraints in cognitive architectures Niels Taatgen and John Anderson
    Part III. Computational Modeling of Various Cognitive Functionalities and Domains:
    7. Computational models of episodic memory Kenneth Norman, Greg Detre, and Sean Polyn
    8. Computational models of semantic memory Timothy Rogers
    9. Models of categorization John Kruschke
    10. Micro-process models of decision making Jerome Busemeyer and Joseph Johnson
    11. Models of inductive reasoning Evan Heit
    12. Mental logic, mental models, and simulations of human deductive reasoning Philip Johnson-Laird and Yingrui Yang
    13. Computational models of skill acquisition Stellan Ohlsson
    14. Computational models of implicit learning Axel Cleeremans and Zoltan Dienes
    15. Computational models of attention and cognitive control Nicola De Pisapia, Grega Repov and Todd Braver
    16. Computational models of developmental psychology Thomas Shultz and Sylvain Sirois
    17. Computational models of psycholinguistics Nick Chater and Morten Christiansen
    18. Computational models in personality and social psychology Stephen Read and Brian Monroe
    19. Cognitive social simulation Ron Sun
    20. Models of scientific explanation Paul Thagard and Abninder Litt
    21. Cognitive modeling for cognitive engineering Wayne Gray
    22. Models of animal learning and their relations to human learning Francisco Lopez and David Shanks
    23. Computational modeling of visual information processing Pawan Sinha and Benjamin Balas
    24. Models of motor control Ferdinando Mussa-Ivaldi and Sara Solla
    Part IV. Concluding Remarks:
    25. An evaluation of computational modeling in cognitive science Margaret Boden
    26. Putting the pieces together again Aaron Sloman.

  • Editor

    Ron Sun
    Dr. Ron Sun is Professor of Cognitive Science at Rensselaer Polytechnic Institute. A well-known researcher in the field of cognitive science, Sun explores the fundamental structure of the human mind and aims for the synthesis of many interesting intellectual ideas into one coherent model of cognition. The goal is to form a generic cognitive architecture that captures a variety of cognitive processes in a unified way and thus to provide unified explanations for a wide range of cognitive data. To do so, for the past two decades, he has been advocating the use of hybrid connectionist-symbolic systems in developing cognitive models and he has been developing theories of human skill learning and human everyday reasoning as the centerpieces of the cognitive architecture.

    Contributors

    Ron Sun, Michael Thomas, James McClelland, Thomas Griffiths, Charles Kemp, Joshua Tenenbaum, Gregor Schoener, Selmer Bringsjord, Niels Taatgen, John Anderson, Kenneth Norman, Greg Detre, Sean Polyn, Timothy Rogers, John Kruschke, Jerome Busemeyer, Joseph Johnson, Evan Heit, Philip Johnson-Laird, Yingrui Yang, Axel Cleeremans, Zoltan Dienes, Nicola De Pisapia, Grega Repovs, Todd Braver, Thomas Shultz, Sylvain Sirois, Nick Chater, Morten Christiansen, Stephen Read, Brian Monroe, Paul Thagard, Abninder Litt, Wayne Gray, Francisco Lopez, David Shanks, Pawan Sinha, Benjamin Balas, Ferdinando Mussa-Ivaldi, Sara Solla, Aaron Sloman

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