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  • Book
  • © 2008

Classic Works of the Dempster-Shafer Theory of Belief Functions

  • Collects the key original contributions that are widely recognized in the field of Dempster-Shafer Theory of Belief functions

  • Authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 219)

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  • ISBN: 978-3-540-44792-4
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Softcover Book USD 399.99
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Hardcover Book USD 399.99
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Table of contents (30 chapters)

  1. Axioms for Probability and Belief-Function Propagation

    • Prakash P. Shenoy, Glenn Shafer
    Pages 499-528
  2. Bayesian Updating and Belief Functions

    • Jean-Yves Jaffray
    Pages 555-576
  3. Belief-Function Formulas for Audit Risk

    • Rajendra P. Srivastava, Glenn R. Shafer
    Pages 577-618
  4. Representation of Evidence by Hints

    • Jürg Kohlas, Paul-André Monney
    Pages 665-681
  5. The Transferable Belief Model

    • Philippe Smets, Robert Kennes
    Pages 693-736
  6. Logicist Statistics II: Inference

    • Arthur P. Dempster
    Pages 761-786
  7. Back Matter

    Pages 787-806

About this book

This book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. By bridging fuzzy logic and probabilistic reasoning, the theory of belief functions has become a primary tool for knowledge representation and uncertainty reasoning in expert systems. This book will serve as the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. From over 120 nominated contributions, the editors selected 30 papers, which are widely regarded as classics and will continue to make impacts on the future development of the field. The contributions are grouped into seven sections, including conceptual foundations, theoretical perspectives, theoretical extensions, alternative interpretations, and applications to artificial intelligence, decision-making, and statistical inferences. The book also includes a foreword by Dempster and Shafer reflecting the development of the theory in the last forty years, and an introduction describing the basic elements of the theory and how each paper contributes to the field.

Keywords

  • Bayesian inference
  • Mathematica
  • artificial intelligence
  • decision making
  • decision theory
  • economics
  • expert system
  • fuzzy
  • fuzzy logic
  • fuzzy set
  • fuzzy sets
  • intelligence
  • probability
  • statistics
  • uncertainty

Editors and Affiliations

  • Machine Intelligence Institute, Iona College, New Rochelle, USA

    Roland R. Yager

  • Department of Management and Information Systems, University of Akron College of Business Administration, 351 Akron, USA

    Liping Liu

Bibliographic Information

Buying options

eBook USD 309.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-44792-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 399.99
Price excludes VAT (USA)
Hardcover Book USD 399.99
Price excludes VAT (USA)