Inference procedures under uncertainty for the problem-reduction method

Mitsuru Ishizuka, K. S. Fu, James T P Yao

Research output: Contribution to journalArticle

92 Citations (Scopus)

Abstract

From the viewpoint of efficient utilization of human knowledge in complex decision-making problems, the inference procedure under uncertainty is becoming more important for the problem-reduction method and expert systems. Unlike intuitive procedures employed so far in some expert systems, rational inference procedures are described in this paper on the basis of established Bayesian theory and Dempster and Shafer's theory of evidence. These results are extended to include fuzzy knowledge. As an alternative to the two probabilistic approaches which require idealized assumptions, fuzzy reasoning is introduced.

Original languageEnglish
Pages (from-to)179-206
Number of pages28
JournalInformation Sciences
Volume28
Issue number3
DOIs
Publication statusPublished - 1982
Externally publishedYes

Fingerprint

Reduction Method
Expert systems
Expert System
Uncertainty
Theory of Evidence
Fuzzy Reasoning
Decision making
Probabilistic Approach
Intuitive
Decision Making
Alternatives
Inference
Knowledge
Expert system

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Statistics, Probability and Uncertainty
  • Electrical and Electronic Engineering
  • Statistics and Probability

Cite this

Inference procedures under uncertainty for the problem-reduction method. / Ishizuka, Mitsuru; Fu, K. S.; Yao, James T P.

In: Information Sciences, Vol. 28, No. 3, 1982, p. 179-206.

Research output: Contribution to journalArticle

Ishizuka, Mitsuru ; Fu, K. S. ; Yao, James T P. / Inference procedures under uncertainty for the problem-reduction method. In: Information Sciences. 1982 ; Vol. 28, No. 3. pp. 179-206.
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