Builds on classical probability theory and offers an extremely workable solution to the many problems of artificial intelligence, concentrating on the rapidly growing areas of fuzzy reasoning and neural computing. Contains a collection of previously unpublished articles by leading researchers in the field.
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Builds on classical probability theory and offers an extremely workable solution to the many problems of artificial intelligence, concentrating on the rapidly growing areas of fuzzy reasoning and neural computing. Contains a collection of previously unpublished articles by leading researchers in the field.
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Inside This Book
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First Sentence:
Several mathematical models have been proposed for the modeling of someone's degrees of belief. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
evidential mapping, conditional belief functions, bpa functions, lower probabilities model, nonzero valuation, generalized mass distributions, canonical hint, linear utility theory, heuristic rule set, expected utility interval, fusion with respect, transferable belief model, title vector, basic belief masses, belief function formalism, multivariate belief functions, same message space, joint valuation, using belief functions, belief function propagation, belief function theory, expected value interval, comparative beliefs, basic probability assignment, propagating belief functions Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Morgan Kaufmann, San Mateo, School of Business, University of Kansas, Princeton University Press, Academic Press, Technical Report, General Systems, Dry Trickle, Libre de Bruxelles, Los Angeles, Harvard University, Menlo Park, Research Report, Sixth Conf, Witness Evidence, Department of Statistics, Lecture Notes, University of Bristol, Annals of Mathematical Statistics, Boca Raton, Englewood Cliffs, Green Drill, Information Sciences New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Several mathematical models have been proposed for the modeling of someone's degrees of belief. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
evidential mapping, conditional belief functions, bpa functions, lower probabilities model, nonzero valuation, generalized mass distributions, canonical hint, linear utility theory, heuristic rule set, expected utility interval, fusion with respect, transferable belief model, title vector, basic belief masses, belief function formalism, multivariate belief functions, same message space, joint valuation, using belief functions, belief function propagation, belief function theory, expected value interval, comparative beliefs, basic probability assignment, propagating belief functions Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Morgan Kaufmann, San Mateo, School of Business, University of Kansas, Princeton University Press, Academic Press, Technical Report, General Systems, Dry Trickle, Libre de Bruxelles, Los Angeles, Harvard University, Menlo Park, Research Report, Sixth Conf, Witness Evidence, Department of Statistics, Lecture Notes, University of Bristol, Annals of Mathematical Statistics, Boca Raton, Englewood Cliffs, Green Drill, Information Sciences New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 8
books:
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48
books
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- Uncertainty in Artificial Intelligence (Volume 4 of Machine Intelligence and Pattern Recognition) (Vol 1) by R. K. Ghatnagar on page 33, page 67, and page 131
- Artificial Intelligence (3rd Edition) by Winston on page 304, and page 574
- Reasoning About Knowledge by Ronald Fagin on page 234
- Mathematical Analysis by Wiley on page 67
- New Mexico (Rookie Read-About Geography) by Cynthia Walker in Copyright
See all 8 books this book cites
- Transactions on Rough Sets I (Lecture Notes in Computer Science / Transactions on Rough Sets) on page 56, page 77, and page 252
- Qualitative and Quantitative Practical Reasoning: First International Joint Conference on Qualitative and Quantitative Practical Reasoning, ... / Lecture Notes in Artificial Intelligence) by Dov Gabbay on page 106, page 182, and page 209
- Rough-Neuro-Computing by Sankar Kumar Pal on page 34, page 488, and page 514
- Belief Functions in Business Decisions (Studies in Fuzziness and Soft Computing) by Rajendra P. Srivastava on page 213, page 243, and page 331
- Handbook of Defeasible Reasoning and Uncertainty Management (Handbook of Defeasible Reasoning and Uncertainty Management Systems) by Dov M. Gabbay on page 24, and page 301
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