A comparison of fuzzy and annotated logic programming

Abstract

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 (RGA-programs) 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.