A methodology for uncertainty in knowledge-based systems
Author(s)
Bibliographic Information
A methodology for uncertainty in knowledge-based systems
（Lecture notes in computer science, 419 . Lecture notes in artificial intelligence）
Springer-Verlag, c1990
- : gw
- : us
Available at / 58 libraries
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Library, Research Institute for Mathematical Sciences, Kyoto University数研
L/N||LNCS||41990006890
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Research Institute for Economics & Business Administration (RIEB) Library , Kobe University図書
: us621.34-446-419s081000083252*
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University of Tsukuba Library, Library on Library and Information Science
: gw007.08:L-49:419901000330
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Note
Includes bibliographical references
Description and Table of Contents
Description
In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.
Table of Contents
The aims of this study.- Interval estimation of probabilities.- Related theories.- The simplest case of a diagnostic system.- Generalizations.- Interval estimation of probabilities in diagnostic systems.- A demonstration of the use of interval estimation.
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