Abstract
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.