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A Note on Ziarko’s Variable Precision Rough Set Model and Nonmonotonic Reasoning

  • Tetsuya Murai
  • Masayuki Sanada
  • Y. Kudo
  • Mineichi Kudo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3066)

Abstract

Granular reasoning is a way of reasoning using granularized possible worlds and lower approximation in rough set theory. However, it can deal only with monotonicity. Then, the extended lower approximation in Ziarko’s variable precision rough set model is introduced to describe nonmonotonic reasoning.

Keywords

Granular reasoning Variable precision rough set model Nonmonotonicity 

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References

  1. 1.
    Chellas, B.F.: Modal Logic: An Introduction. Cambridge University Press, Cambridge (1980)zbMATHGoogle Scholar
  2. 2.
    Lin, T.Y.: Granular Computing on Binary Relation I: Data Mining and Neighborhood Systems, II: Rough Set Representations and Belief Functions. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 1: Methodology and Applications, pp. 107–121, 122–140. Physica-Verlag (1998)Google Scholar
  3. 3.
    Murai, T., Nakata, M., Sato, Y.: A Note on Filtration and Granular Reasoning. In: Terano, T., Nishida, T., Namatame, A., Tsumoto, S., Ohsawa, Y., Washio, T. (eds.) JSAI-WS 2001. LNCS (LNAI), vol. 2253, pp. 385–389. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  4. 4.
    Murai, T., Resconi, G., Nakata, M., Sato, Y.: Operations of Zooming In and Out on Possible Worlds for Semantic Fields. In: Damiani, E., et al. (eds.) Knowledge-Based Intelligent Information Engineering Systems and Allied Technologies, pp. 1083–1087. IOS Press, Amsterdam (2002)Google Scholar
  5. 5.
    Murai, T., Resconi, G., Nakata, M., Sato, Y.: Granular Reasoning Using Zooming In & Out: Part 2. Aristotle’s Categorical Syllogism. Electronical Notices in Theoretical Computer Science 82(4), Elsevier (2003)Google Scholar
  6. 6.
    Murai, T., Resconi, G., Nakata, M., Sato, Y.: Granular Reasoning Using Zooming In & Out: Part 1. Propositional Reasoning. In: Proceedings of International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. LNCS (LNAI), Springer, Heidelberg (2003) (to appear)Google Scholar
  7. 7.
    Pawlak, Z.: Rough Sets. International Journal of Computer and Information Sciences 11, 341–356 (1982)zbMATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer, Dordrecht (1991)zbMATHGoogle Scholar
  9. 9.
    Skowron, A.: Toward Intelligent Systems: Calculi of Information Granules. In: Terano, T., Nishida, T., Namatame, A., Tsumoto, S., Ohsawa, Y., Washio, T. (eds.) JSAI-WS 2001. LNCS (LNAI), vol. 2253, pp. 251–260. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  10. 10.
    Ziarko, W.: Variable Precision Rough Set Model. Journal of Computer and System Sciences 11, 39–59 (1993)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Tetsuya Murai
    • 1
  • Masayuki Sanada
    • 1
  • Y. Kudo
    • 2
  • Mineichi Kudo
    • 1
  1. 1.Graduate School of EngineeringHokkaido UnivSapporoJapan
  2. 2.Muroran Institute of TechnologyMuroranJapan

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