Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 1990
ISBN 10: 3540973435 ISBN 13: 9783540973430
Language: English
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Add to basketHardcover. Condition: Très bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Légères traces d'usure sur la couverture. Salissures sur la tranche. Couverture différente. Edition 1990. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisat ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slightly creased cover. Slight signs of wear on the cover. Stains on the edge. Different cover. Edition 1990. Ammareal gives back up to 15% of this item's net price to charity organizations.
Published by New York, Springer, 1990
Language: English
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Published by Springer-verlag New York Inc., 1990
ISBN 10: 0387973435 ISBN 13: 9780387973432
Language: English
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Published by Springer-Verlag New York Inc., 2012
ISBN 10: 1461264502 ISBN 13: 9781461264507
Language: English
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Add to basketCondition: New. Series: Symbolic computation/Artificial Intelligence. Num Pages: 285 pages, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 16. Weight in Grams: 462. . 2012. Softcover reprint of the original 1st ed. 1990. Paperback. . . . .
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Published by Springer-Verlag New York Inc., 1990
ISBN 10: 0387973435 ISBN 13: 9780387973432
Language: English
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Add to basketCondition: New. Talks about reasoning with causal associations during diagnostic problem-solving. This book develops a mathematical model called parsimonious covering theory and links it with probability theory. Series: Symbolic computation/Artificial Intelligence. Num Pages: 285 pages, biography. BIC Classification: UYA; UYQ. Category: (G) General (US: Trade); (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 17. Weight in Grams: 597. . 1990. Hardback. . . . .
Published by Springer-Verlag New York Inc., New York, NY, 1990
ISBN 10: 0387973435 ISBN 13: 9780387973432
Language: English
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Add to basketHardcover. Condition: new. Hardcover. This book is about reasoning with causal associations during diagnostic problem-solving. It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result is a mathematical model of diagnostic reasoning called parsimonious covering theory. Within this diagnostic, problems and important relevant concepts are formally defined, properties of diagnostic problem-solving are identified and analyzed, and algorithms for finding plausible explanations in different situations are given along with proofs of their correctness. Another feature of this book is the integration of parsimonious covering theory and probability theory. Based on underlying cause-effect relations, the resulting probabilistic causal model generalized Bayesian classification to diagnostic problems where multiple disorders (faults) may occur simultaneously. Both sequential best-first search algorithms and parallel connectionist (neural network) algorithms for finding the most probable hypothesis are provided. This book should appeal to both theoretical researchers and practitioners.For researchers in artificial intelligence and cognitive science, it provides a coherent presentation of a new theory of diagnostic inference. For engineers and developers of automated diagnostic systems or systems solving other abductive tasks, the book may provide useful insights, guidance, or even directly workable algorithms. This would seem to indicate that many of the essential aspects of diagnostic reasoning are a type of intuiti- based, common sense reasoning. More precisely, diagnostic reasoning can be classified as a type of inf- ence known as abductive reasoning or abduction. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Springer-Verlag New York Inc., 2012
ISBN 10: 1461264502 ISBN 13: 9781461264507
Language: English
Seller: Kennys Bookstore, Olney, MD, U.S.A.
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Add to basketCondition: New. Series: Symbolic computation/Artificial Intelligence. Num Pages: 285 pages, biography. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 16. Weight in Grams: 462. . 2012. Softcover reprint of the original 1st ed. 1990. Paperback. . . . . Books ship from the US and Ireland.
Published by Springer-Verlag New York Inc., 1990
ISBN 10: 0387973435 ISBN 13: 9780387973432
Language: English
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Add to basketCondition: New. Talks about reasoning with causal associations during diagnostic problem-solving. This book develops a mathematical model called parsimonious covering theory and links it with probability theory. Series: Symbolic computation/Artificial Intelligence. Num Pages: 285 pages, biography. BIC Classification: UYA; UYQ. Category: (G) General (US: Trade); (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 17. Weight in Grams: 597. . 1990. Hardback. . . . . Books ship from the US and Ireland.
Published by Springer-Verlag New York Inc., New York, NY, 1990
ISBN 10: 0387973435 ISBN 13: 9780387973432
Language: English
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Add to basketHardcover. Condition: new. Hardcover. This book is about reasoning with causal associations during diagnostic problem-solving. It formalizes several currently vague notions of abductive inference in the context of diagnosis. The result is a mathematical model of diagnostic reasoning called parsimonious covering theory. Within this diagnostic, problems and important relevant concepts are formally defined, properties of diagnostic problem-solving are identified and analyzed, and algorithms for finding plausible explanations in different situations are given along with proofs of their correctness. Another feature of this book is the integration of parsimonious covering theory and probability theory. Based on underlying cause-effect relations, the resulting probabilistic causal model generalized Bayesian classification to diagnostic problems where multiple disorders (faults) may occur simultaneously. Both sequential best-first search algorithms and parallel connectionist (neural network) algorithms for finding the most probable hypothesis are provided. This book should appeal to both theoretical researchers and practitioners.For researchers in artificial intelligence and cognitive science, it provides a coherent presentation of a new theory of diagnostic inference. For engineers and developers of automated diagnostic systems or systems solving other abductive tasks, the book may provide useful insights, guidance, or even directly workable algorithms. This would seem to indicate that many of the essential aspects of diagnostic reasoning are a type of intuiti- based, common sense reasoning. More precisely, diagnostic reasoning can be classified as a type of inf- ence known as abductive reasoning or abduction. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Making a diagnosis when something goes wrong with a natural or m- made system can be difficult. In many fields, such as medicine or electr- ics, a long training period and apprenticeship are required to become a skilled diagnostician. During this time a nov.
Seller: moluna, Greven, Germany
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Making a diagnosis when something goes wrong with a natural or m- made system can be difficult. In many fields, such as medicine or electr- ics, a long training period and apprenticeship are required to become a skilled diagnostician. During this time a nov.