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Automated learning of rules using genetic operators

  • C. -E. Liedtke
  • Th. Schnier
  • A. Bloemer
Knowledge Representation and Learning
Part of the Lecture Notes in Computer Science book series (LNCS, volume 719)

Abstract

The configuration system CONNY permits the automated configuration of image analysis processes which includes the selection of the appropriate sequence of operators and the adaptation of the free parameters. The system uses explicitly formulated knowledge contents from a human image analysis expert coded as rules of a rule based system. In the present contribution it has been investigated if and to which extent the rules can be learned automatically. The approach which has been chosen is based on the selection and valuation of individual rules and on the manipulation and generation of new rules by the use of genetic operators. The advantageous capabilities of a learning approach using genetic operators is demonstrated.

Keywords

Automated learning genetic operators explicit knowledge representation knowledge based systems rule based systems system configuration image processing expert systems CONNY 

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References

  1. 1.
    C.-E. Liedtke, A. Bloemer, Th. Gahm: ”Knowledge Based Configuration of Image Segmentation Processes”, International Journal of Imaging Systems and Technology, Vol. 2, 285–295 (1990)69.Google Scholar
  2. 2.
    C.-E. Liedtke, A. Bloemer: ”Architecture of the Knowledge Based Configuration System for Image Analysis CONNY”,11th IAPR, International Conference on Pattern Recognition, den Haag, 1992.Google Scholar
  3. 3.
    John H. Holland: Escaping Brittleness: ”The possibilities of General-Purpose Learning Algorithms Applied to Parallel Rule-Based Systems, Machine Learning II”, Morgan Kaufman Publishers Inc, Los Altos, 1986.Google Scholar
  4. 4.
    Th. Schnier: ”Untersuchung der Eignung genetischer Algorithmen zum Erlernen hochsprachlicher Regeln für die wissensbasierte Konfiguration von Bildanalyseprozessen”, Diplomarbeit am Institut für Theoretische Nachrichtentechnik und Informationsverarbeitung der Universität Hannover, April 1992.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • C. -E. Liedtke
    • 1
  • Th. Schnier
    • 1
  • A. Bloemer
    • 1
  1. 1.Institut für Theoretische Nachrichtentechnik und InformationsverarbeitungUniversität HannoverHannover 1Germany

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