Differentiating problem solving methods

  • Guus Schreiber
  • Bob Wielinga
  • Hans Akkermans
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 599)


Problem solving methods (PSM's) are important in constructing modular and reusable knowledge-based systems, as they specify the different types of knowledge used in knowledge-based reasoning, as well as under what circumstances what knowledge is to be applied. We argue that the formal modeling of PSM's is a useful means for clarifying, communicating and comparing problem-solving knowledge. This paper shows how such PSM's can be formally defined. We illustrate this by developing a formal model for the Cover- and-Differentiate method for diagnosis, and comparing this to Heuristic Classification.


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  1. Akkermans, H., van Harmelen, F., Schreiber, G., & Wielinga, B. (1991). A formalisation of knowledge-level models for knowledge acquistion. International Journal of Intelligent Systems. forthcoming.Google Scholar
  2. Bergstra, J., Heering, J., & Klint, P. (1990). Module algebra. Journal of the ACM, 37(2):335–372.CrossRefGoogle Scholar
  3. Breuker, J., Wielinga, B., van Someren, M., de Hoog, R., Schreiber, G., de Greef, P., Bredeweg, B., Wielemaker, J., Billault, J.-P., Davoodi, M., & Hayward, S. (1987). Model Driven Knowledge Acquisition: Interpretation Models. ESPRIT Project P1098 Deliverable D1 (task A1), University of Amsterdam and STL Ltd.Google Scholar
  4. Clancey, W. (1983). The epistemology of a rule based system-a framework for explanation. Artificial Intelligence, 20:215–251. Also: Stanford Heuristic Programming Project, Memo HPP-81-17, November 1981, also numbered STAN-CS-81-896.CrossRefGoogle Scholar
  5. Clancey, W. (1985). Heuristic classification. Artificial Intelligence, 27:289–350.CrossRefGoogle Scholar
  6. Eshelman, L. (1988). MOLE: A knowledge-acquisition tool for cover-and-differentiate systems. In Marcus, S., editor, Automating Knowledge Acquisition for Expert Systems, pages 37–80. Kluwer Academic Publishers, The Netherlands.Google Scholar
  7. Eshelman, L., Ehret, D., McDermott, J., & Tan, M. (1988). MOLE: a tenacious knowledge acquisition tool. In Boose, J. & Gaines, B., editors, Knowledge Based Systems, Volume 2: Knowledge Acquisition Tools for Expert Systems, pages 95–108, London. Academic Press.Google Scholar
  8. Jackson, P., Reichgelt, H., & van Harmelen, F. (1989). Logic-Based Knowledge Representation. The MIT Press, Cambridge, MA.Google Scholar
  9. Lavrač, N. & Vassilev, H. (1989). Meta-level architecture of a second-generation knowledge acquisition system. In Morik, K., editor, Proceedings EWSL-89, pages 99–109, London. Pitman.Google Scholar
  10. McDermott, J. (1988). Preliminary steps towards a taxonomy of problem-solving methods. In Marcus, S., editor, Automating Knowledge Acquisition for Expert Systems, pages 225–255. Kluwer Academic Publishers, The Netherlands.Google Scholar
  11. Steels, L. (1990). Components of expertise. AI Magazine. Also as: AI Memo 88-16, AI Lab, Free University of Brussels.Google Scholar
  12. van Harmelen, F., Akkermans, H., Balder, J., Schreiber, G., & Wielinga, B. (1990). Formal specifications of knowledge models. ESPRIT Basic Research Action P3178 REFLECT, Technical Report RFL/ECN/I.4/1, Netherlands Energy Research Foundation ECN.Google Scholar
  13. Weyhrauch, R. (1980). Prolegomena to a theory of mechanized formal reasoning. Artificial Intelligence, 13. Also in: Readings in Artificial Intelligence, Webber, B.L. and Nilsson, N.J. (eds.), Tioga publishing, Palo Alto, CA, 1981, pp. 173–191. Also in: Readings in Knowledge Representation, Brachman, R.J. and Levesque, H.J. (eds.), Morgan Kaufman, California, 1985, pp. 309–328.Google Scholar
  14. Wielinga, B. & Breuker, J. (1986). Models of expertise. In Proceedings ECAI-86, pages 306–318.Google Scholar
  15. Wielinga, B. J., Schreiber, A. T., & Breuker, J. A. (1992). KADS: A modelling approach to knowledge engineering. Knowledge Acquisition, 4(1). Special issue “The KADS approach to knowledge engineering”.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Guus Schreiber
    • 1
  • Bob Wielinga
    • 1
  • Hans Akkermans
    • 2
  1. 1.Department of Social Science InformaticsUniversity of AmsterdamWB AmsterdamThe Netherlands
  2. 2.Software Engineering & Research DepartmentNetherlands Energy Research Foundation ECNPettenThe Netherlands

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