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Synopsis
The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in- creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for- malisms. In this book, we offer a broad perspective on uncertainty and approach- es to managing uncertainty. Rather than provide a daunting mass of techni- cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl- edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di- rections in the field. The intended readership will include researchers and practitioners in- volved in the design and implementation of Decision Support Systems, Ex- pert Systems, other Knowledge-Based Systems and in Cognitive Science.
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- ÉditeurSpringer
- Date d'édition1993
- ISBN 10 0792324331
- ISBN 13 9780792324331
- ReliureRelié
- Langueanglais
- Nombre de pages277
- Coordonnées du fabricantnon disponible
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Representing Uncertain Knowledge: An Artificial Intelligence Approach
Edité par
Kluwer Academic, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
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Etat : Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:0792324331. N° de réf. du vendeur 9462739
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Representing Uncertain Knowledge : An Artificial Intelligence Approach
Edité par
Springer Netherlands, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Ancien ou d'occasion
Couverture rigide
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 292 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 3023177/202
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Representing Uncertain Knowledge
Edité par
Springer Netherlands, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
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Representing Uncertain Knowledge
Edité par
Springer Netherlands Okt 1993, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for malisms. In this book, we offer a broad perspective on uncertainty and approach es to managing uncertainty. Rather than provide a daunting mass of techni cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di rections in the field. The intended readership will include researchers and practitioners in volved in the design and implementation of Decision Support Systems, Ex pert Systems, other Knowledge-Based Systems and in Cognitive Science. 292 pp. Englisch. N° de réf. du vendeur 9780792324331
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Representing Uncertain Knowledge: An Artificial Intelligence Approach
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Representing Uncertain Knowledge
Edité par
Springer Netherlands, Springer Netherlands Okt 1993, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for malisms. In this book, we offer a broad perspective on uncertainty and approach es to managing uncertainty. Rather than provide a daunting mass of techni cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di rections in the field. The intended readership will include researchers and practitioners in volved in the design and implementation of Decision Support Systems, Ex pert Systems, other Knowledge-Based Systems and in Cognitive Science.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 292 pp. Englisch. N° de réf. du vendeur 9780792324331
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Representing Uncertain Knowledge : An Artificial Intelligence Approach
Edité par
Springer Netherlands, Springer Netherlands, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for malisms. In this book, we offer a broad perspective on uncertainty and approach es to managing uncertainty. Rather than provide a daunting mass of techni cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di rections in the field. The intended readership will include researchers and practitioners in volved in the design and implementation of Decision Support Systems, Ex pert Systems, other Knowledge-Based Systems and in Cognitive Science. N° de réf. du vendeur 9780792324331
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Representing Uncertain Knowledge: An Artificial Intelligence Approach
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
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Representing Uncertain Knowledge: An Artificial Intelligence Approach
Edité par
Kluwer Academic Pub, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Neuf
Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Representing Uncertain Knowledge: An Artificial Intelligence Approach
Edité par
Springer, 1993
ISBN 10 : 0792324331
ISBN 13 : 9780792324331
Ancien ou d'occasion
Couverture rigide
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