Bilattice Logic for Rough Sets

Author:

Nakayama Yotaro,Akama Seiki,Murai Tetsuya, , ,

Abstract

Rough set theory is studied to manage uncertain and inconsistent information. Because Pawlak’s decision logic for rough sets is based on the classical two-valued logic, it is inconvenient for handling inconsistent information. We propose a bilattice logic as the deduction basis for the decision logic of rough sets to address inconsistent and ambiguous information. To enhance the decision logic to bilattice semantics, we introduce Variable Precision Rough Set (VPRS). As a deductive basis for bilattice decision logic, we define a consequence relation for Belnap’s four-valued semantics and provide a bilattice semantic tableau TB4 for a deduction system. We demonstrate the soundness and completeness of TB4 and enhance it with weak negation.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference27 articles.

1. Z. Pawlak, “Rough Sets: Theoretical Aspects of Reasoning about Data,” Kluwer Academic Publishers, 1991.

2. W. Ziarko, “Variable precision rough set model,” J. of Computer and System Science, Vol.46, No.1, pp. 39-59, 1993.

3. R. M. Smullyan, “First-Order Logic,” Dover Books, 1995.

4. R. Hähnle, “Automated deduction in multiple-valued logics,” Oxford University Press, 1995.

5. M. D’Agostino, “Investigations into the Complexity of some Propositional calculi,” Oxford University Computing Laboratory, Programming Research Group, 1990.

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