Activation of Fuzzy Rules in RETE Network

  • Zenon A. Sosnowski
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 7)


A central algorithm in rule-based expert systems is the pattern matching among rule predicates and current data. Systems like OPS5 and its various derivatives use the RETE algorithm for this function. This paper describes and analyses augmentations of the basic RETE algorithm that are incorporated into an experimental fuzzy expert system shell FuzzyCLIPS which contains the capabilities of handling fuzzy concepts and reasoning. The new concept of fuzzy RETE network allows all fuzzy rules, with the same linguistic variable, to be activated whenever fuzzy evidence concerning that variable is asserted into to the working memory.


Expert System Fuzzy Number Fuzzy Rule Linguistic Variable Condition Element 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    E.H.Shortliffe. Computer-based Medical Consultation: MYCIN. American Elsevier, New York, 1976.Google Scholar
  2. 2.
    B.G. Buchanan, E.H.Shortliffe. Rule-Based Expert Systems. Addison-Wesley, Reading, Mass.,1984.Google Scholar
  3. 3.
    G.Shafer. A Mathematical Theory of Evidence. Princeton University Press, Princeton, N.J., 1976Google Scholar
  4. 4.
    K.P. Adlassing, G.Kolarz. „Representation and semiautomatic acquisition of medical knowledge in Cadiag-1 and Cadiag-2“. Computer and Biomedical Research, 19, 63–79, 1988.CrossRefGoogle Scholar
  5. T.Whalen, B.Schott, F.Ganoe. „Fault diagnosis in fuzzy network“. Proc. 1982 Int. Conf. Cybernetics and Society. IEEE Press, New York, 1982.Google Scholar
  6. 6.
    J.Buckley, W.Siler. „Fuzzy operators for possibility interval set“. Fuzzy Sets and Systems, 22, 215–27, 1987.MathSciNetCrossRefGoogle Scholar
  7. 7.
    K.S.Leung, W.S.F.Wong, W.Lam. „Application of a novel fuzzy expert system shell“. Expert Systems, 6, 2–10, 1989.CrossRefGoogle Scholar
  8. 8.
    Z.A.Sosnowski. „FLIPS-a language for processing fuzzy data“. Fuzzy Sets and Systems,37 23–32, 1990. 209Google Scholar
  9. 9.
    J. Pan, G. N. DeSouza, and A. C. Kak, „FuzzyShell: A Large-Scale Expert System Shell Using Fuzzy Logic for Uncertainty Reasoning“, IEEE Trans. Fuzzy Syst., 6, 563–581, 1998.CrossRefGoogle Scholar
  10. 10.
    Artificial Intelligence Section, Lyndon B.Johnson Space Center. CLIPS Reference Manual, Version 4. 3, May 1989.Google Scholar
  11. Artificial Intelligence Section, Lyndon B.Johnson Space Center. CLIPS Advanced Programming Guide, Version 4. 3, May 1989Google Scholar
  12. C.L. Forgy. The OPS5 User Manual. Technical Report, CMU-CS-79–132, Computer Science Department, Carnegie- Mellon University, 1981.Google Scholar
  13. C.L. Forgy. „RETE: A fast algorithm for the many pattern/many object pattern match problem“. Artificial Intelligence, 19, 17–37, 1982.CrossRefGoogle Scholar
  14. Z.A. Sosnowski. „A fuzzy extension of CLIPS rule-based shell“. Fuzzy Engineering toward Human Friendly Systems, vol.1, 503–512, 1991. 15. National Research Council, Canada, FuzzyCLIPS Version 6.04A User’s Guide, 1998.Google Scholar
  15. L.A. Zadeh. „Fuzzy sets“. Information and control, 8, 338–383, 1965.Google Scholar
  16. L.A. Zadeh. „ The concept of a linguistic variable and its application to approximate reasoning“. Infor. Sci., 8, 395–460, 1975.Google Scholar
  17. 18.
    Z.A.Sosnowski. „ A linguistic variable in FLIPS programming language“. The Second Joint IFSAEC end EURO-WG Workshop ‘Progress in Fuzzy Sets in Europe’,April 6–8 1988, Vienna, pp. 71–74.Google Scholar
  18. A.Kaufman, M.M.Gupta, Introduction to Fuzzy Arithmetic. Theory and Applications, Van Nostrand Reinhold, 1985.Google Scholar
  19. M.Cayrol, H.Farency and H.Prade. „Fuzzy pattern matching“. Kybernetes, 11, 103–106, 1982.Google Scholar
  20. M.Mizumoto, S.Fukami, K.Tanaka. „Some methods of fuzzy reasoning“. In M.M.Gupota, R.K.Ragade and R.R.Yager, editors, Advances in Fuzzy Set Theory and Applications, pp. 117–136. North-Holland, Amsterdam, 1976.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Zenon A. Sosnowski
    • 1
  1. 1.Department of Computer ScienceTechnical University of BialystokBialystokPoland

Personalised recommendations