A comparison of fuzzy and annotated logic programming

The aim of this paper is to contribute to the study of relationships between different formalism for handling uncertainty in logic programming, knowledge-based systems and deductive databases. Generalized annotated programs with restricted semantics (RGAprograms) are well suited to fit real-world data. We show that RGA-programs with constant annotations in body are equivalent to programs with left discontinuous annotation and with possibly non-computable semantics. Our model of fuzzy logic programming (FLP) can well handle recursive programs. We show that FLP has the same expressive power as RGA-programs without constant annotations in body of rules. We introduce several syntactical transformations of programs and study their models and production operators. We introduce a new efficient procedural semantics for RGA-programs and show connections between different sorts of computed answers.