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GAITS: Fuzzy sets-based algorithms for computing strategies using genetic algorithms

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Fuzzy Logic in Artificial Intelligence (FLAI 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 695))

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Abstract

This paper introduces a new method combining Fuzzy Logic and Genetic Algorithms to allow Intelligent Tutoring Systems to be efficient. We consider supervised teaching where the teacher assigns a initial profile and a finale profile to each student before starting the teaching. The system computes an optimal strategy which represents a way of evolving the student's knowledge from the initial profile. So, the student's knowledge will change progressively to reach the final profile where the teaching objective is judged to be reached. The paper deals with an example presenting a simulation of the result's of a good student and a bad one.

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References

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Author information

Authors and Affiliations

  1. IRIN, Université de Sciences et des Techniques de Nantes, France

    Mohamed Quafafou

  2. Digital Equipment Corporation, Sophia-Antipolis, France

    Mohammed Nafia

Authors
  1. Mohamed Quafafou
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  2. Mohammed Nafia
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Editor information

Erich P. Klement Wolfgang Slany

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© 1993 Springer-Verlag Berlin Heidelberg

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Quafafou, M., Nafia, M. (1993). GAITS: Fuzzy sets-based algorithms for computing strategies using genetic algorithms. In: Klement, E.P., Slany, W. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1993. Lecture Notes in Computer Science, vol 695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56920-0_8

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  • DOI: https://doi.org/10.1007/3-540-56920-0_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56920-6

  • Online ISBN: 978-3-540-47782-2

  • eBook Packages: Springer Book Archive

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