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The use of possibilistic logic PL1 in a customizable tool for the generation of production-rule based systems

  • Guilherme Bittencourt
  • Maurício Marengoni
  • Sandra Sandri
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 747)

Abstract

A theoretical framework is proposed, in which possibilistic logic can be uniformly used to treat uncertainty associated with production rules, when knowledge is represented in either logic or frames. This model is being implemented in the uncertainty module of a tool designed to allow the construction of expert system shells.

Keywords

Expert System Knowledge Representation Possibilistic Logic Knowledge Representation Language Expert System Shell 
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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References

  1. 1.
    Buchanan B.G., Shortliffe E.H., Rule-Based Expert Systems, the MYCIN Experiments of the Stanford Heuristics Programming Project. Addison Wesley, 1984.Google Scholar
  2. 2.
    Bobrow D.G., Winograd T., “An Overview of KRL, A Knowledge Representation Language”. Cognitive Science, Vol. 1, No. 1, pp. 3–46, 1977.Google Scholar
  3. 3.
    Laurent J.-P., Thome F., Ayel J., Ziebelin D., “KEE, Knowledge Craft et Art: Evaluation comparative de trois outils de développement de systèmes experts”. Revue d'Intelligence Artificielle, Vol. 1, No. 2, pp. 25–53, 1987.Google Scholar
  4. 4.
    Bittencourt G. “A Hybrid System Architecture and its Unified Semantics”. In Proc. 4th Int. Symp. on Methodologies for Intelligent Systems (Z.W. Ras, ed); North-Holland, pp. 150–157, Charlotte, NC, 1989.Google Scholar
  5. 5.
    Calmet J.; Tjandra O.; Bittencourt G. “MANTRA: A Shell for Hybrid Knowledge Representation”. Proc. 3rd Int. Conf. on Tools for Artif. Intel., San José, Ca, 1991.Google Scholar
  6. 6.
    Brownston L., Farrel R., Kanr E., Martin N., Programming Expert Systems in OPS-5, An Introduction to Rule-Based Programming. Addison Wesley, Reading, Ma, 1985.Google Scholar
  7. 7.
    Buchanan B.G., Feigenbaum E.A., “DENDRAL and Meta-DENDRAL: Their Applications Dimension”. Artificial Intelligence, Vol. 11, No. 1–2, pp. 5–24, 1978.Google Scholar
  8. 8.
    Van Melle W., Shortliffe E.H., Buchanan B.G., “EMYCIN A Domain Independent System that Aids in Constructing Knowledge-Based Consultation Programs”. In State of the Art Report on Machine Intelligence, New York, Pergamon, Infotech, 1981.Google Scholar
  9. 9.
    Bittencourt G., Marengoni M., “A Customizable Tool for the Generation of Production-Based Systems”. Proc. 8th Int. Conf. on Artificial Intelligence in Engineering, pp. 337–352, Toulouse, France, 1993.Google Scholar
  10. 10.
    Dubois D., Lang J., Prade H., Possibilistic Logic. Report IRIT/91-98/R, IRIT, Toulouse, France, 1991.Google Scholar
  11. 11.
    Minsky M., “A Framework to Represent Knowledge”. In The Psychology of Computer Vision, (P. Winston, ed), McGraw-Hill, pp. 211–277, 1975.Google Scholar
  12. 12.
    Quillian, M.R., “Semantic Memory”. In Semantic Information Processing, (M.L. Minsky, ed), pp. 216–270, M.I.T. Press, Cambridge, Ma, 1968.Google Scholar
  13. 13.
    Dubois D., Prade H. (with the collaboration of H. Farreny, R. Martin-Clouaire, C. Testemale), Possibility Theory — An Approach to the Computerized Processing of Uncertainty. Plenum Press, 1988.Google Scholar
  14. 14.
    Davis R., King J., “An Overview of Production Systems”. Machine Intelligence, vol 8, pp. 300–332, 1977.Google Scholar
  15. 15.
    Silva, F. de A.T.F. da, “A Hybrid Formalism for Representation and Interpretation of Image Knowledge”. Proc. Int. Soc. for Photogrammetry and Remote Sensing Congress, Washington, DC, 1992.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Guilherme Bittencourt
    • 1
  • Maurício Marengoni
    • 1
  • Sandra Sandri
    • 1
  1. 1.Instituto Nacional de Pesquisas Espaciais - INPESão José dos CamposSP-Brazil

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