• DocumentCode
    920564
  • Title

    Knowledge representation in fuzzy logic

  • Author

    Zedeh, L.A.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA
  • Volume
    1
  • Issue
    1
  • fYear
    1989
  • fDate
    3/1/1989 12:00:00 AM
  • Firstpage
    89
  • Lastpage
    100
  • Abstract
    The author presents a summary of the basic concepts and techniques underlying the application of fuzzy logic to knowledge representation. He then describes a number of examples relating to its use as a computational system for dealing with uncertainty and imprecision in the context of knowledge, meaning, and inference. It is noted that one of the basic aims of fuzzy logic is to provide a computational framework for knowledge representation and inference in an environment of uncertainty and imprecision. In such environments, fuzzy logic is effective when the solutions need not be precise and/or it is acceptable for a conclusion to have a dispositional rather than categorical validity. The importance of fuzzy logic derives from the fact that there are many real-world applications which fit these conditions, especially in the realm of knowledge-based systems for decision-making and control
  • Keywords
    fuzzy logic; knowledge representation; computational system; control; decision-making; fuzzy logic; imprecision; inference; knowledge representation; knowledge-based systems; meaning; real-world applications; uncertainty; Artificial intelligence; Calculus; Computer science; Fuzzy logic; Humans; Intelligent networks; Knowledge representation; Logic testing; Uncertainty; Unemployment;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.43406
  • Filename
    43406