Survey of the Problem-Solving Type Classification

  • Frank Puppe


The term classification (diagnostics) is given to the solution procedure for problems with the following properties:
  1. 1.

    The domain consists of two finite, disjunctive sets-one containing observations and the other problem solutions-and of typically uncertain, complex knowledge about the relationships between these two sets.

  2. 2.

    A problem is defined by a given subset of observations, which may be incomplete.

  3. 3.

    The result of the classification is the selection of one or more solutions to the problem.

  4. 4.

    If the quality of the solution can be improved by considering additional observations, one of the tasks of classification is to determine which additional observations are to be requested.



Problem Type Decision Table Knowledge Type Uncertain Knowledge Uncertain Observation 
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. Achtstätter, J.: Diagnostic Expert Systems in Circuit Board Production (in German), in [Puppe 89], 3.28–329, 1989.Google Scholar
  2. Aikins, J., Kunz, J., Shortliffe, E. and Fallat, R: PUFF: An Expert System for Interpretation of Pulmonary Function Data, Computers in Biomedical Research, 16, 199–208, 1983.CrossRefGoogle Scholar
  3. Aikins, J., Kunz, J., Shortliffe, E. and Fallat, R: PUFF: An Expert System for Interpretation of Pulmonary Function Data, Clancey, W. and Shortliffe, E. (eds.): Readings in Medical Artificial Intelligence, Chap. 19, Addison-Wesley, 1984.Google Scholar
  4. Borrmann, H.-P. and Winklhofer, F.: Expert System for Early Damage Detection in Turhomachinery (in German), Qualität und Zuverlässigkeit, 33, 139–141, 1988.Google Scholar
  5. Dickmann, H.-J.: Tuning of Data Bank Applications (in German), Praxis der Informationsverarbeitung und Kommunikation, 9, 122–126, 1986.CrossRefGoogle Scholar
  6. Elstein, A., Shulman, L. and Sprafka, S.: Problem Solving, Harvard University Press, 1978.Google Scholar
  7. Ernst, G.: Expert Systems in the Motor Test Bed - Application Report in Bläsing, J. (ed.): Practical Handbook of Quality Control, Vol. 4 (in German), Baustein F2, GMFT, 1988.Google Scholar
  8. Fagan, L., Kunz, J., Feigenbaum, E. and Osborn, J.: Extensions to the Rule-Based Formalism for a Monitoring Task, in in Buchanan, B. and Shortliffe, E. (eds.): Rule-Based Expert Systems, Chap. 22, Addison-Wesley, 1984.Google Scholar
  9. Gasching, J.: PROSPECTOR: an Expert System for Mineral Exploration, in Michie, D. (ed.): Introductionary Readings in Expert Systems, Gordon and Breech, 1982.Google Scholar
  10. Keim, M. and Nordmann, R.: Application of an Expert System for Diagnosis of Rotordynamic Problems in Turbomachinery, Proceedings of the American Society of Mechanical Engineering (ASME), Design Technical Conference on Mechanical Vibrations and Noise (DE-VOL-18/5), 85–91, 1989.Google Scholar
  11. Mertens, P., Borkowski, V. and Geis, W.: Industrial Expert System Applications - a Compendium (in German), Springer, 2nd edition, 1990.Google Scholar
  12. Miller, R., Pople, H. and Myers, J.: INTERNISTl, an Experimental Computer-Based Diagnostic Consultant for General Internal Medicine, New England Journal of Medicine 307, 468–476, 1982.CrossRefGoogle Scholar
  13. Miller, R., McNeil, M., Challinaor, S., Masari, F. and Myers, J.: The INTERNIST1/ Quick Medical Reference Project - a Status Report, West J. Med. 145, 816–822, 1986.Google Scholar
  14. Miitter, S.: FAKT A - a System for the Construction and Evaluation of Diagnostic Case Data Banks and its Application to the Example of an Advising System for Data Banks (in German), Diploma Thesis, University of Karlsruhe, 1989.Google Scholar
  15. Nedeß, C. and Plog, J.: EFFEKT - Diagnostic Expert System for the Spray Casting of Elastomers (in German), Kunststoffe 78, No. 12, 1988.Google Scholar
  16. Neis, B.: PID A S - Development and Evaluation of an Expert System for the Identification of Fungi (in German), Diploma Thesis, University of Kaiserslautern, 1988.Google Scholar
  17. Nossem, B.: Multiple Sclerosis Expert Systems (in German), Dissertation, University of Erlangen-Niirnberg, 1989.Google Scholar
  18. Plog, J.: Expert System Supported Quality Control in the Production of Elastomer Particles (in German), Fortschrittsberichte VDI, Reihe 2: Fertigungstechnik, No. 200, VDI-Verlag, 1990.Google Scholar
  19. Premauer, T.: IXMO - an Expert System for Motor Diagnostics in the Automobile Industry (in German), INTERKAMA-86, Fachberichte für Messen, Steuern, Regeln 14, 532–539, Springer, 1986.Google Scholar
  20. Puppe, F.: Experience from three Application Projects with MED1 (in German), GI-Kongreß Wissensbasierte Systeme, Springer Informatik-Fach berichte 112, 234–245, 1985 (a).Google Scholar
  21. Puppe, B. and Puppe, F: MED1 - an Intelligent Computer Program for Thoracic Pain Diagnosis, Klinische Wochenschrift 63, 511–517, 1985 (b).Google Scholar
  22. Puppe, F.: Diagnostic Problem Solving with Expert Systems (in German), Springer Informatik-Fachberichte 148, 1987.Google Scholar
  23. Puppe, F. and Voss, H.: Abstracts on Diagnostic Expert Systems, Collected Contributions to the 1st and 2nd Workshops Diagnostic Expert Systems (in German), Arbeitspapiere der GMD 375, 1989.Google Scholar
  24. Puppe, F., Legleitner, T. and Huber, K.: DAX/MED2 - A Diagnostic Expert System for Quality Assurance of an Automatic Transmission Control Unit, in Zarri, G. (ed.): Operational Expert Systems in Europe, Pergammon Press, 1991.Google Scholar
  25. Schewe, S., Herzer, P. and Krüger, K.: Prospective Application of an Expert System for the Medical History of Joint Pain, Klinische Wochenschrift, 1990.Google Scholar
  26. Shortliffe, E., Computer-Based Medical Consultations: MYCIN, American Elsevier, 1976.Google Scholar
  27. Trendelenburg, Chr. and Wieland, H.: Routine Use of a Clinical Chemistry Expert System with a Knowledge Base on Disorders in Lipoprotein Metabolism, Biochim. Clin. 10, 928–929, 1986.Google Scholar
  28. Walser, P.: Formalization of Heuristic, Causal, Case-Based and General Knowledge for a Tutorial Diagnostic Expert System Exemplified with the Automobile Motor Domain (in German), Diploma Thesis, University of Karlsruhe, Institute of Logic, 1991.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Frank Puppe
    • 1
  1. 1.Institut für Informatik Lehrstuhl für Künstliche Intelligenz Am HublandUniversität WürzburgWürzburgGermany

Personalised recommendations