• DocumentCode
    1803946
  • Title

    Genetics-based self-adjusting expert systems

  • Author

    Pakath, Ramakrishnan

  • Author_Institution
    Dept. of Decision Sci. & Inf. Syst., Kentucky Univ., Lexington, KY, USA
  • fYear
    1993
  • fDate
    5-8 Jan 1993
  • Firstpage
    344
  • Abstract
    The conventional rule-based expert system (ES) paradigm has been criticized because of its inability to display characteristics of true intelligence and its relatively static knowledge storehouse and dependence on rote-learned rule fragments as a basis for reasoning. An approach to constructing self-adjusting ESs is described. Self-adjusting ESs are characterized by their dynamic knowledge bases that improve with experience and their ability to pursue unfocused reasoning. An implementation of the paradigm is examined and its traits in light of the criticisms leveled against its predecessor are evaluated
  • Keywords
    expert systems; inference mechanisms; self-adjusting systems; dynamic knowledge bases; genetics-based ES; self-adjusting ESs; self-adjusting expert systems; unfocused reasoning; Business; Displays; Educational institutions; Electronic switching systems; Expert systems; Information systems; Learning systems; Machine learning; Medical expert systems; Scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences, 1993, Proceeding of the Twenty-Sixth Hawaii International Conference on
  • Conference_Location
    Wailea, HI
  • Print_ISBN
    0-8186-3230-5
  • Type

    conf

  • DOI
    10.1109/HICSS.1993.284330
  • Filename
    284330