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Uncertainty Representation in Knowledge Based Systems

  • H. -J. Zimmermann
  • B. Werners
Conference paper
Part of the Lecture Notes in Engineering book series (LNENG, volume 53)

Abstract

Fuzzy Set Theory as proposed by L. Zadeh in 1965 is adaptable to different problem structures and well suited to model human evaluation and decision making processes. If uncertainty enters into models, it is classically of the stochastic kind which can properly be modelled by using probability theory. There are other fields, however, in which the description of problems contains uncertainties, in which, however, they are of a different kind than randomness. One of the most important areas of this kind is probably that of human problem solving and decision making: here the human factor enters with all its vaguenesses of perception, of subjectivity, of attitudes of goals and conceptions. To use a modeling language which is dichotomous in this area seems far from adequate.

Keywords

Membership Function Fuzzy Logic Expert System Linguistic Variable Inference Engine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin, Heidelberg 1989

Authors and Affiliations

  • H. -J. Zimmermann
    • 1
  • B. Werners
    • 1
  1. 1.RWTH AachenAachenGermany

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