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A New Perspective on Reasoning with Fuzzy Rules

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Advances in Soft Computing — AFSS 2002 (AFSS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2275))

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Abstract

Fuzzy rules are conditional pieces of knowledge which can either express constraints on the set of values which are left possible for a variable, given the values of other variables, or accumulate tuples of feasible values. The first type are implicative rules, while the second are based on conjunctions. Consequences of this view on inference and interpolation between sparse rules are presented.

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References

  1. A. Ayoun and M. Grabisch. Tracks real-time classification based on fuzzy rules. International Journal of Intelligent Systems, 12:865–876, 1997.

    Article  Google Scholar 

  2. B. Bouchon-Meunier, J. Delechamp, C. Marsala, N. Mellouli, M. Rifqi, and L. Zerrouki. Analogy and fuzzy interpolation in case of sparse rules. In Proc. of the EUROFUSE-SIC Joint Conference, pages 132–136, 1999.

    Google Scholar 

  3. B. Bouchon-Meunier, D. Dubois, L. Godo, and H. Prade. Fuzzy sets and possibility theory in approximate and plausible reasoning. In J. Bezdek, D. Dubois, and H. Prade, editors, Fuzzy sets in approximate reasoning and information systems, The Handbooks of Fuzzy Sets, pages 15–190. Kluwer, Boston, 1999.

    Google Scholar 

  4. B. Bouchon-Meunier, D. Dubois, C. Marsala, H. Prade, and L. Ughetto. A comparative view of interpolation methods between sparse fuzzy rules. In Proc. of the Joint 9th IFSA World Congress and 20th NAFIPS International Conference, volume 5, pages 2499–2504, 2001.

    Google Scholar 

  5. B. Bouchon-Meunier, C. Marsala, and M. Rifqi. Interpolative reasoning based on graduality. In Proc. of 9th Int. conf. on fuzzy systems (FUZZ-IEEE’2000), pages 483–487, 2000.

    Google Scholar 

  6. A. Di Nola, W. Pedrycz, and S. Sessa. An aspect of discrepancy in the implementation of modus ponens in the presence of fuzzy quantities. International Journal of Approximate Reasoning, 3:259–265, 1989.

    Article  MATH  MathSciNet  Google Scholar 

  7. D. Dubois, M. Grabisch, and H. Prade. Gradual rules and the approximation of control laws. In H.T. Nguyen, M. Sugeno, R. Tong, and R.R. Yager, editors, Theoretical Aspects of Fuzzy Control, pages 147–181. Wiley, 1994.

    Google Scholar 

  8. D. Dubois, P. Hajek, and H. Prade. Knowledge driven vs. data driven logics. Journal of Logic, Language and Information, 9:65–89, 2000.

    Article  MATH  MathSciNet  Google Scholar 

  9. D. Dubois, E. Hüllermeier, and H. Prade. Flexible control of case based prediction in the framework of possibility theory. In Proc. of the 5th Eur. Work. on CBR (EWCBR’00), pages 61–73. LNCS 1898— Springer Verlag, 2000.

    Google Scholar 

  10. D. Dubois, H. Prade, and L. Ughetto. Checking the coherence and redundancy of fuzzy knowledge bases. IEEE Transactions on Fuzzy Systems, 5(3):398–417, 1997.

    Article  Google Scholar 

  11. D. Dubois, H. Prade, and L. Ughetto. Fuzzy logic, control engineering and arti ficial intelligence. In H.B. Verbruggen, H.-J. Zimmermann, and R. Babuska, editors, Fuzzy Algorithms for Control Engineering, pages 17–57. Kluwer Academic Publishers, 1999.

    Google Scholar 

  12. D. Dubois and H. Prade. Fuzzy rules in knowledge-based systems— modeling gradedness, uncertainty and preference. In R.R. Yager and L.A. Zadeh, editors, An Introduction to Fuzzy Logic Applications in Intelligent Systems, pages 45–68. Kluwer Academic Publishers, 1992.

    Google Scholar 

  13. D. Dubois and H. Prade. What are fuzzy rules and how to use them. Fuzzy Sets and Systems, 84(2):169–186, 1996.

    Article  MATH  MathSciNet  Google Scholar 

  14. D. Dubois and H. Prade. On fuzzy interpolation. International Journal of General Systems, 28:103–114, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  15. E.H. Mamdani and S. Assilian. An experiment in linguistic synthesis with a fuzzy logic controller. International Journal on Man-Machine Studies, 7:1–13, 1975.

    Article  MATH  Google Scholar 

  16. J. Mendel. Fuzzy logic systems for engineering: A tutorial. Proc. IEEE-Special issue on fuzzy logic with engineering applications, 83(3):345–377, 1995.

    Google Scholar 

  17. L. Ughetto, D. Dubois, and H. Prade. Fuzzy interpolation by convex completion of sparse rule bases. In Proc. of 9th Int. conf. on fuzzy syst. (FUZZ-IEEE’2000), pages 465–470, 2000.

    Google Scholar 

  18. L. Ughetto, D. Dubois, and H. Prade. Interpolation lin aire par ajout de r gles dans une base incompl te. In Proc. Rencontres Francophones sur la Logique Floue et ses Applications (LFA’00), pages 71–78. Cépaduès, Toulouse, 2000.

    Google Scholar 

  19. L.A. Zadeh. The concept of a linguistic variable and its application to approximate reasoning. Information Sciences, 1975. Part 1: 8:199–249; Part 2: 8:301-357; Part 3: 9:43-80.

    Article  MathSciNet  Google Scholar 

  20. L.A. Zadeh. The calculus of fuzzy if-then rules. AI Expert, 7(3):23–27, 1992.

    Google Scholar 

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Author information

Authors and Affiliations

  1. IRIT— CNRS, Université Paul Sabatier, 31062, Toulouse Cedex 4, France

    D. Dubois & H. Prade

  2. IRIN, Université de Nantes, BP 92208, 44322, Nantes Cedex 3, France

    L. Ughetto

Authors
  1. D. Dubois
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  2. H. Prade
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  3. L. Ughetto
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Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, 700108, Calcutta, India

    Nikhil R. Pal

  2. Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Japan

    Michio Sugeno

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© 2002 Springer-Verlag Berlin Heidelberg

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Dubois, D., Prade, H., Ughetto, L. (2002). A New Perspective on Reasoning with Fuzzy Rules. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_1

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  • DOI: https://doi.org/10.1007/3-540-45631-7_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43150-3

  • Online ISBN: 978-3-540-45631-5

  • eBook Packages: Springer Book Archive

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