Heuristic Classification: Additional Mechanisms

  • Frank Puppe


In the previous chapter we discussed how to deal with the central requirements of heuristic classification, namely the treatment of uncertain knowledge, step-wise abstraction and dialog control. In this chapter the mechanisms for the remaining requirements of Sect. 13.3 are described: the treatment of uncertain, subjective, potentially false, incomplete and parametrizable knowledge, of multiple solutions and combined recommendations for several solutions. The basic structure developed in Chap. 15 will be assumed.


Solution Class Knowledge Representation Multiple Solution Belief Revision Competitor Relationship 
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. de Kleer, J.: An Assumption Based TMS, AI Journal 28, 127–162, 1986.Google Scholar
  2. Pearl, J.: How to Do with Probabilities What People Say You Can’t, Technical Report CSD 85003, University of California, and Proceedings of the 2nd Conference on Artificial Intelligence Applications, 1985.Google Scholar
  3. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, 1988.Google Scholar
  4. Puppe, F.: Diagnostic Problem Solving with Expert Systems (in German), Springer Informatik-Fachberichte 148, 1987.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