Mathematical Models for Handling Partial Knowledge in Artificial Intelligence

Editors: Coletti, Giulianella, Dubois, Didier, Scozzafava, R. (Eds.)

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About this book

Knowledge acquisition is one of the most important aspects influencing the quality of methods used in artificial intelligence and the reliability of expert systems. The various issues dealt with in this volume concern many different approaches to the handling of partial knowledge and to the ensuing methods for reasoning and decision making under uncertainty, as applied to problems in artificial intelligence. The volume is composed of the invited and contributed papers presented at the Workshop on Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, held at the Ettore Majorana Center for Scientific Culture of Erice (Sicily, Italy) on June 19-25, 1994, in the framework of the International School of Mathematics "G.Stampacchia". It includes also a transcription of the roundtable held during the workshop to promote discussions on fundamental issues, since in the choice of invited speakers we have tried to maintain a balance between the various schools of knowl­ edge and uncertainty modeling. Choquet expected utility models are discussed in the paper by Alain Chateauneuf: they allow the separation of perception of uncertainty or risk from the valuation of outcomes, and can be of help in decision mak­ ing. Petr Hajek shows that reasoning in fuzzy logic may be put on a strict logical (formal) basis, so contributing to our understanding of what fuzzy logic is and what one is doing when applying fuzzy reasoning.

Table of contents (20 chapters)

  • Ellsberg Paradox Intuition and Choquet Expected Utility

    Chateauneuf, Alain

    Pages 1-20

  • Fuzzy Logic as Logic

    Hájek, Petr

    Pages 21-30

  • Mathematical Foundations of Evidence Theory

    Kohlas, Jürg

    Pages 31-64

  • Semantics for Uncertain Inference Based on Statistical Knowledge

    Kyburg, Henry E., Jr.

    Pages 65-81

  • Prospects and Problems in Applying the Fundamental Theorem of Prevision as an Expert System: An Example of Learning About Parole Decisions

    Lad, Frank (et al.)

    Pages 83-100

Buy this book

eBook $139.00
price for USA in USD (gross)
  • ISBN 978-1-4899-1424-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $215.00
price for USA in USD
  • ISBN 978-0-306-45076-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA in USD
  • ISBN 978-1-4899-1426-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Mathematical Models for Handling Partial Knowledge in Artificial Intelligence
Editors
  • Giulianella Coletti
  • Didier Dubois
  • R. Scozzafava
Copyright
1995
Publisher
Springer US
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4899-1424-8
DOI
10.1007/978-1-4899-1424-8
Hardcover ISBN
978-0-306-45076-1
Softcover ISBN
978-1-4899-1426-2
Edition Number
1
Number of Pages
IX, 308
Number of Illustrations and Tables
3 b/w illustrations
Topics