| Description |
1 online resource (xxi, 1270 pages) : illustrations. |
| Physical Medium |
polychrome |
| Description |
text file |
| Series |
Bradford Books
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Bradford book.
|
| Note |
"A Bradford book." |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
1. Role of knowledge in discourse comprehension: a construction-integration model / Walter A. Kintssch -- 2. Act: a simple theory of complex cognition / John R. Anderson -- 3. Preliminary analysis of the soar architecture as a basis for general intelligence / Paul S. Rosenbloom, John E. Laird, Allen Newell, and Robert McCarl -- 4. Adaptive executive control: flexible multiple-task performance without pervasive immutable response-selection bottlenecks / David E. Meyer [and others] -- 5. Capacity theory of comprehension: individual differences in working memory / Marcel A. Just and Patricia A. Carpenter -- 6. How neural networks learn from experience / Geoffrey E. Hinton -- 7. Hopfield model / John Hertz, Anders Krogh, and Richard G. Palmer -- 8. Learning representations by back-propagating errors / David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams -- 9. Forward models: supervised learning with a distal teacher / Michael I. Jordan and David E. Rumelhart -- 10. Finding structure in Time / Jeffrey L. Elman -- 11. Self-organizing neural network for supervised learning, recognition, and prediction / Gail A. Carpenter and Stephen Grossberg -- 12. Optimality: from neural networks to universal grammar / Alan Prince and Paul Smolensky -- 13. Dynamic binding in a neural network for shape recognition / John E. Hummel and Irving Biederman -- 15. End of the line for a brain-damaged model of unilateral neglect / Michael C. Mozer, Peter W. Halligan, and John C. Marshall -- 16. Integrated theory of list memory / John R. Anderson, Dan Bothell, Christian Lebiere, and Michael Matessa -- 17. Why there are complementary learning systems in hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory / James L. McClelland, Bruce L. McNaughton, and Randall C. O'Reilly -- 18. ALCOVE: an exemplar-based connectionist model of category learning / John K. Kruschke -- 19. How people learn to skip steps / Stephen B. Blessing and John R. Anderson -- 20. Acquisition of children's addition strategies: a model of impasse-free, knowledge-level learning / Randolph M. Jones and Kurt Van Lehn -- 21. Learning from a connectionist model of the acquisition of the English past tense / Kim Plunkett and Virginia A. Marchman -- 22. Acquiring the mapping from meaning to sounds / Garrison W. Cottrell and Kim plunkett -- 23. Understanding normal and impaired word reading: computational principles in quasi-regular domains / David C. Plaut, James L. McClelland, Mark S. Seidenberg, and Karalyn Patterson -- 24. Language production and serial order: a functional analysis and a model / Gary S. Dell, Lisa K. Burger, and William R. Svec -- 25. Interference in short-term memory: the magical number two (or three) in sentence processing / Richard L. Lewis -- 26. Similarity, interactive activation, and mapping: an overview / Robert L. Goldstone and Douglas L. Medin -- 27. Analogical mapping by constraint satisfaction / Keith J. Holyoak and Paul Thagard -- 28. MAC/FAC: a model of similarity-based retrieval / Kenneth D. Forbus, Dedre Gentner, and Keith Law -- 29. Distributed representations of structure: a theory of analogical access and mapping / John E. Hummel and Keith J. Holyoak -- 30. Case-based learning: predictive features in indexing / Colleen M. Seifert [and others] -- 31. Feature-based induction / Steven A. Sloman -- 32. Deduction as verbal reasoning / Thad A. Polk and Allen Newell -- 33. Project Ernestine: validating a GOMS analysis for predicting and explaining real-world task performance / Wayne D. Gray, Bonnie E. John, and Michael E. Atwood -- 34. Connectionism and the problem of systematicity (continued): why Smolensky's solution still doesn't work / Jerry Fodor -- 35. Networks and theories: the place of connectionism in cognitive science / Michael C. McCloskey -- 36. Neuropsychological inference with an interactive brain: a critique of the "locality" assumption / Martha J. Farah -- 37. Is human cognition adaptive? / John R. Anderson -- 38. Précis of Unified Theories of Cognition / Allen Newell. |
| Summary |
Annotation Computational modeling plays a central role in cognitive science. This book provides a comprehensive introduction to computational models of human cognition. It covers major approaches and architectures, both neural network and symbolic; major theoretical issues; and specific computational models of a variety of cognitive processes, ranging from low-level (e.g., attention and memory) to higher-level (e.g., language and reasoning). The articles included in the book provide original descriptions of developments in the field. The emphasis is on implemented computational models rather than on mathematical or nonformal approaches, and on modeling empirical data from human subjects. |
| Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
| Language |
English. |
| Subject |
Cognition.
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Cognition. |
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Cognitive science.
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Cognitive science. |
| Genre/Form |
Electronic books.
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Electronic books.
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Handboeken (vorm)
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| Added Author |
Polk, Thad A.
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Seifert, Colleen M.
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| Other Form: |
Print version: Cognitive modeling. Cambridge, Mass. : MIT Press, ©2002 0262161982 (DLC) 2001018325 (OCoLC)45791410 |
| ISBN |
0585442789 (electronic book) |
|
9780585442785 (electronic book) |
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9780262281744 (electronic book) |
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0262281740 (electronic book) |
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0262161982 |
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9780262161985 |
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0262661160 (paperback ; alkaline paper) |
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9780262661164 (paperback ; alkaline paper) |
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