The rationality and decidability of fuzzy implications

Authors:
Cheng Xiaochun;Jiang Yunfei;Liu Xuhua
Affiliations:
Open Lab for Symbolic Computation and Knowledge Engineering, Department of Computer Science, Jilin University, Changchun, P. R. China;Open Lab for Symbolic Computation and Knowledge Engineering, Department of Computer Science, Jilin University, Changchun, P. R. China;Open Lab for Symbolic Computation and Knowledge Engineering, Department of Computer Science, Jilin University, Changchun, P. R. China
Venue:
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Year:
1995

Citing 3
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Abstract

It is well known that knowledge-based systems would be more robust and smarter if they can deal with the inconsistent, incomplete or imprecise knowledge, which has been referred to as common sense knowledge. In this paper, we discuss fuzzy implications in the sense of common sense reasoning. Firstly, we analyse the rationality of some existing fuzzy implications based on the discussion of implicational paradoxes. Secondly, we present a new fuzzy preferential implication that is nonmonotonic, paraconsistent and without the general implicational paradoxes. Finally, we propose sound and complete decision tableaux of such implications, which can be used as the inference engines of adaptive expert systems or frameworks for the fuzzy Prolog.