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Approximate decision logic and reduction of decision rules

Shrabonti G., Alam S. S.

Foundations of Computing and Decision Sciences

2003

Vol. 28, No. 1

3-16

This paper generalises Pawlak's rough approach to Reduction of Decision Rules using Decision Logic language (DL-language) by introducing Approximate Decision Logic language (ADL-language) based on almost indiscernibility relation. An information system has been considered where attribute values are not always quantitative, rather subjective having vague or imprecise meanings. Some objects may have attribute values which are almost identical. This observation has been analysed here based on fuzzy proximity relations on different domains of attributes.

On Modal and Fuzzy Decision Logics Based on Rough Set Theory

Fan T-F., Liau C.J., Yao Y.

Fundamenta Informaticae

2002

Vol. 52, nr 4

323-344

Some modal decision logic languages are proposed for knowledge representation in data mining through the notions of models and satisfiability. The models are collections of data tables consisting of a finite set of objects described by a finite set of attributes. Some relationships may exist between data tables in a collection and the modalities of our languages are interpreted with respect to these relations in Kripkean style semantics. The notion of fuzzy decision logic is also reviewed and combined with the modal decision logic. The combined logic is shown to be useful in the representation of fuzzy sequential patterns.

A possibilistic decision logic with applications

Liau C.J., Liu D.R.

Fundamenta Informaticae

2001

Vol. 46, nr 3

199-217

In this paper, we investigate a knowledge representation formalism in the context of fuzzy data tables. A possibilistic decision logic incorporating linguistic terms is proposed for representing and reasoning about knowledge in fuzzy data tables. Two applications based on the logic are described. The first is the extraction of fuzzy rules from general fuzzy data tables. In this application, the knowledge in the tables may be made explicit by the formulas of the logic or used implicitly in decision-making. The second is for the fuzzy quantization problem of precise data tables. It can be viewed as a special case of the first, however, due to some special properties of the problem, a polynomial time rule extraction process can be obtained. Finally, the relationship of the logic with some works for handling uncertain information in data tables is also discussed.