COMPARISON OF ROUGH-SET AND INTERVAL-SET MODELS FOR UNCERTAIN REASONING

Comparison of Rough-Set and Interval-Set Models for Uncertain Reasoning

In the rough-set model, a set is represented by a pair of ordinary sets called the lower and upper approximations. In the interval-set model, a pair of sets is referred to as the lower and upper bounds which define a family of sets. A significant difference between these models lies in the definition and interpretation of their extended set-theoretic operators. The operators in the rough-set mo...

Generalized Rough Set Models

Modal Reasoning and Rough Set Theory

In this paper, we would like to present some modal logics with semantics based on rough set theory and related notions. In addition to surveying some well-known results about the links between modal logics and rough set theory, we also develop some new applied logics inspired I)y generalized rough set theory. Kcywor(ls: Rough set, modal logic, cpistcmic logic. 1 I n t r o d u c t i o n Tile rou...

Decision-Theoretic Rough Set Models

Decision-theoretic rough set models are a probabilistic extension of the algebraic rough set model. The required parameters for defining probabilistic lower and upper approximations are calculated based on more familiar notions of costs (risks) through the well-known Bayesian decision procedure. We review and revisit the decision-theoretic models and present new results. It is shown that we nee...

Reasoning about Data - A Rough Set Perspective

[ Abstract.] The paper contains some considerations concerning the relationship between decision rules and inference rules from the rough set theory perspective. It is shown that decision rules can be interpreted as a generalization of the modus ponens inference rule, however there is an essential difference between these two concepts. Decision rules in the rough set approach are used to descri...