Automated learning of rules using genetic operators

C. E. Liedtke; Th H. Schnier; A. Bloemer

doi:10.1007/3-540-57233-3_44

Details

Original language	English
Title of host publication	Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings
Editors	Dmitry Chetverikov, Walter G. Kropatsch
Pages	327-334
Number of pages	8
Publication status	Published - 1993
Event	5th International Conference on Computer Analysis of Images and Patterns, CAIP 1993 - Budapest, Hungary Duration: 13 Sept 1993 → 15 Sept 1993

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	719 LNCS
ISSN (Print)	0302-9743
ISSN (electronic)	1611-3349

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, CONNY, Expert systems, Explicit knowledge representation, Genetic operators, Image processing, Knowledge based systems, Rule based systems, System configuration

ASJC Scopus subject areas

Cite this

Automated learning of rules using genetic operators. / Liedtke, C. E.; Schnier, Th H.; Bloemer, A.
Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings. ed. / Dmitry Chetverikov; Walter G. Kropatsch. 1993. p. 327-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 719 LNCS).

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Liedtke, CE, Schnier, TH & Bloemer, A 1993, Automated learning of rules using genetic operators. in D Chetverikov & WG Kropatsch (eds), Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 719 LNCS, pp. 327-334, 5th International Conference on Computer Analysis of Images and Patterns, CAIP 1993, Budapest, Hungary, 13 Sept 1993. https://doi.org/10.1007/3-540-57233-3_44

Liedtke, C. E., Schnier, T. H., & Bloemer, A. (1993). Automated learning of rules using genetic operators. In D. Chetverikov, & W. G. Kropatsch (Eds.), Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings (pp. 327-334). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 719 LNCS). https://doi.org/10.1007/3-540-57233-3_44

Liedtke CE, Schnier TH, Bloemer A. Automated learning of rules using genetic operators. In Chetverikov D, Kropatsch WG, editors, Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings. 1993. p. 327-334. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-57233-3_44

Liedtke, C. E. ; Schnier, Th H. ; Bloemer, A. / Automated learning of rules using genetic operators. Computer Analysis of Images and Patterns - 5th International Conference, CAIP 1993, Proceedings. editor / Dmitry Chetverikov ; Walter G. Kropatsch. 1993. pp. 327-334 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Research@Leibniz University