Using a blackboard architecture in a distributed DBMS environment: An expert system application

  • Mary McLeish
  • Matt Cecile
  • Alex Lopez-Suarez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 420)


This paper discusses the use of a blackboard control structure to co-ordinate various tasks involved in the operation of a medical diagnostic system. A number of methodologies are used to extract rules from a large database of statistical information. An ORACLE DBMS running on a SEQUENT parallel machine forms the core of the data management component. A natural integration of the DBMS with this blackboard planning strategy is outlined.


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  1. 1.
    Adlassnig, K.P. Fuzzy Set Theory in Medical Diagnosis. IEEE Transactions on Systems, Man and Cybernectics, Vol. 16, 1986, pp. 260–265.Google Scholar
  2. 2.
    Bond, A.H., Gasser, L. “Readings in Distributed Artificial Intelligences”, Morgan Kaufmann, 1988.Google Scholar
  3. 3.
    Buchanan, B. and Shortliffe, E. Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley, 1986.Google Scholar
  4. 4.
    Buckles, B.P. and Petry, F.E. A Fuzzy Representation for Relational Databases. Fuzzy Sets and Systems 7, 1982, pp. 213–226.Google Scholar
  5. 5.
    Cecile, M., McLeish, M., Pascoe, P., Taylor, W. Induction and Uncertainty Management Techniques Applied to Veterinary Medical Diagnosis. Uncertainty Management Workshop Proceedings, Minnesota, 1988, pp. 38–48.Google Scholar
  6. 6.
    Cheeseman, P.C. Learning Expert Systems for Data. Proc. Workshop of Knowledge-Based Systems, Denver, December 1984, pp. 115–122.Google Scholar
  7. 7.
    Dempster, A. A Generalization of Bayesian Inference, JRSS, Series B, 1968, pp. 325–339.Google Scholar
  8. 8.
    Ducharme, N., Ducharme, G., Pascoe, P.J., Horney, F.D. Positive Predictive Value of Clinical Explanation in Selecting Medical or Surgical Treatment of Horses with Abdominal Pain. Proc. Equine Colic Res. 1986, pp. 200–230.Google Scholar
  9. 9.
    Engelmore, R., Morgan, T., Blackboard Systems, Addison-Wesley, 1988.Google Scholar
  10. 10.
    Erman, L.D., Hayes-Roth, F., Lesser, V.R. and Reddy, D.R. “The Hearsay-II Speech Understanding System: Integrating Knowledge to Resolve Uncertainty”, Comput. Surv. 12, 213–253 (1980).Google Scholar
  11. 11.
    Good, I.J. Probability and the Weighting of Evidence. New York: Hafner, 1950.Google Scholar
  12. 12.
    Grundy. Cluster-Analysis — A Series of Database Views. Proceedings of the Third International Workshop on Statistical and Scientific Database Management, July, 1986, pp. 208–211.Google Scholar
  13. 13.
    Hayes-Roth, B. A Blackboard Architecture for Control. Artif. Intelligence Journal, 26, 251–321 (1985).Google Scholar
  14. 14.
    Held, J. and Carlis, J. Match: A New High-Level Relational Operator for Pattern Matching. Comm. ACM, 30, 1 (January 1987), pp. 62–75.Google Scholar
  15. 15.
    Kung, R. A Database Management System Base on an Object-Oriented Model. In Expert Database Systems, edited by Kerschberg, L., Addison-Wesley, 1987.Google Scholar
  16. 16.
    Matthews, D. and Farewell, V. Using and Understanding Medical Statistics, Karger Press, 1985.Google Scholar
  17. 17.
    McLeish, M., Cecile, M. and Lopez-Suarez, A. Database Issues for a Veterinary Medical Expert System. Proceedings, 4th International Workshop on Scientific and Statistical Database Management, June 88, pp. 33.48 and Springer-Verlag lecture notes in Computer Science, #339, 1989, pp. 177–192.Google Scholar
  18. 18.
    McLeish, M. Exploring Knowledge Acquisition Tools for a Veterinary Medical Expert System. For the First International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, June 1988, pp. 778–788.Google Scholar
  19. 19.
    McLeish, M. Comparing Knowledge Acquisition and Classical Statistical in the Development of a Veterinary Medical Expert System. The Proceedings of the 20th Symposium on Statistics and Computing, Virginia, April 1988, pp. 346–352.Google Scholar
  20. 20.
    McLeish, M., Cecile, M. Enhancing Medical Expert Systems with Knowledge Obtained from Statistical Data. Accepted, the special issue of Annals of Math and A.I., from A.I. and Statistics Workshop, Jan 89 (the paper also appears in the preprints of this Workshop).Google Scholar
  21. 21.
    McLeish, M., Cecile, M., Yao, P., Stirtzinger, T. “Experiments Using Belief Functions and Weights of Evidence on Statistical Data and Expert Opinions”, Uncertainty Management Workshop Proceedings, Windsor, 1989, pp. 253–265.Google Scholar
  22. 22.
    Minsky, M. and Selfridge, O.G. Learning in Random Nets. Information Theory (ed. Colin Cherry; London Butterworths), pp. 335–347.Google Scholar
  23. 23.
    Patil, R., Schwartz, W. and Szolovitz, P., Sounding Board, Artificial Intelligence in Medicine, New England Journal of Medicine, Vol 16, 1987, pp. 685–688.Google Scholar
  24. 24.
    Pearl, J. Distributed Revision of Composite Beliefs. Artificial Intelligence, Oct. 1987, pp. 173–215.Google Scholar
  25. 25.
    Quinlan, U., Ross. Learning Efficient Classification Procedures and Their Application to Chess End Games. 1983, In Machine Learning: An Artificial Intelligence Approach, edited by Ryszard Michalski, Tioga, pp. 463–482.Google Scholar
  26. 26.
    Raju, K. and Majumdar, A. Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems. Accepted for publication in ACMTODS.Google Scholar
  27. 27.
    Rendell, L. A General Framework for Induction and a Study of Selective Induction. Machine Learning, Kluwar Pub, 1986, vol. 1, pp. 177–226.Google Scholar
  28. 28.
    Rice, James, “The Design of a High Performance Concurrent Problem Solving System”, Knowledge Systems Lab, Stanford, Report #KSL 89-37.Google Scholar
  29. 29.
    Self, M. and Cheeseman, P. Bayesian Prediction of Artificial Intelligence. Proceedings of the Third AAAI Workshop on Uncertainty Management, 1987, pp. 61–69.Google Scholar
  30. 30.
    Spiegelhalter, D.J. and Knill-Jones, R.B. Statistical and Knowledge-based Approaches to Clinical Decision Support Systems, JRSS, B, 147, pp. 35–77.Google Scholar
  31. 31.
    Yager, R.R. A Note on Probabilities of Fuzzy Events. Information Sciences 18, 1979, pp. 113–129.Google Scholar
  32. 32.
    Zadeh, L.A. The Concept of a Linguistic Variable and its Application to Approximate Reasoning — I, II, III. Information Sciences, 1975–1976, pp. 199–249, 301–357, 43–80.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Mary McLeish
    • 1
  • Matt Cecile
    • 1
  • Alex Lopez-Suarez
    • 1
  1. 1.Department of Computing and Information ScienceUniversity of GuelphGuelph

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