×

zbMATH — the first resource for mathematics

On learning in a fuzzy rule-based expert system. (English) Zbl 0862.68109
Summary: The main motivation of adding learning capabilities to fuzzy rule-based expert systems is the desire to reduce the cost and time of knowledge acquisition. Particularly attractive are in this context learning algorithms with the ability to synthesize rules from past cases already available in the database. With the aim of automating knowledge acquisition we present in this article fuzzy classifier systems which integrate a fuzzy rule base, a genetic algorithm and an apportionment of credit function. As a first result we give a variant of the mutation operator which allows us to derive a global convergence result for the generic algorithm under rather weak assumptions. With this approach a combination of the advantage of genetic algorithms and simulated annealing algorithms is achieved.
MSC:
68T35 Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence
68T05 Learning and adaptive systems in artificial intelligence
PDF BibTeX XML Cite
Full Text: Link EuDML
References:
[1] T. Akiyama, T. Sasaki: Extended fuzzy traffic control model on urban expressway. Preprints of Second IFSA Congress 1 (1989), 1, 278 - 279.
[2] G. B. Dantzig: Linear Programming and Extensions. 6th Edition. Priceton University Press, Princeton, NJ 1963. · Zbl 0108.33103
[3] A. Geyer-Schulz: Fuzzy rule-based expert systems. APL Techniques in Expert Systems (J. R. Kraemer and P. C. Berry, ACM SIGAPL, Syracuse, NY 1988. · Zbl 0914.68166
[4] D. E. goldberg: Genetic Algorithms in Search, Optimization & Machine Learning. Addison Wesley, Reading, MA 1989. · Zbl 0721.68056
[5] B. Hajek: Cooling archedules for optimal annealing. Math. Oper. Res. 13 (1988), 13, 311 - 329. · Zbl 0652.65050 · doi:10.1287/moor.13.2.311
[6] R. F. Hartl: Global Convergence Proof for a Class of Genetic Algorithms. Unpublished Manuscript.
[7] K. Hirota Y. Arai, S. Hachisu: Real time pattern recognition and fuzzy controlled robot-arm. Preprints of Second IFSA Congress 1 (1987), 1, 274 - 277.
[8] D. Yasubiko, M. Houma: Improved fuzzy-set temperature distribution control for electric furnace. Preprints of Second IFSA Congress 1 (1987), 1, 270 - 273.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.