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A comparison of fuzzy and annotated logic programming. (English) Zbl 1065.68024
Summary: 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.

68N17 Logic programming
68T37 Reasoning under uncertainty in the context of artificial intelligence
Full Text: DOI
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