Isbn: 9780792324331 - Representing Uncertain Knowledge: an Artificial Intelligence Approach (16 results)

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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    Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.

  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer Netherlands, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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    Condition: New. pp. 292 Index.

  • Language: English

    Published by Kluwer Academic Pub, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

    • Hardcover

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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    Buch. Condition: 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.

  • Language: English

    Published by Springer Netherlands Okt 1993, 1993

    0792324331 / 9780792324331

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    Buch. Condition: 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.

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    Language: English

    Published by Springer Netherland, 1993

    0792324331 / 9780792324331

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    Buch. Condition: Neu. Representing Uncertain Knowledge | An Artificial Intelligence Approach | Dominic Clark (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 1993 | Springer Netherland | EAN 9780792324331 | Verantwortliche Person für die EU: Springer Netherlands, Haberstr. 7, 69126 Heidelberg, buchhandel-buch[at]springer[dot]com | Anbieter: preigu Print on Demand.

  • Language: English

    Published by Springer Netherlands, Springer Netherlands Okt 1993, 1993

    0792324331 / 9780792324331

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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.

  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

    • Hardcover
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    Condition: New. Print on Demand pp. 292 69:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Case Laminate on White w/Gloss Lam.

  • Language: English

    Published by Springer, 1993

    0792324331 / 9780792324331

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    Condition: New. PRINT ON DEMAND pp. 292.