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Descripción
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| In many real-life applications, one needs to handle information that is either imprecise or uncertain, or even both. Since clas-sical symbolic approaches employing two-valued logic are not particularly well-suited for this task, various generalisations to enable the handling of imperfect information have been proposed in the literature. The present thesis takes another step into this direction and studies two fuzzifications of well-studied logic-based formalisms that are used in the field of knowledge representation and rea- soning. The first part presents a multi-adjoint semantics for fuzzy logic programming that is the theoretical foundation of a practical tool, the RFuzzy Framework. A least model semantics, a least fixpoint semantics, and an operational semantics are defined and their equivalence is proved. The second part reports on the prototype of a Fuzzy Description Logic reasoner that has been implemented in the Logic Programming language Prolog. The reasoner is based on a tableaux algorithm for Fuzzy ALC, but can be extended to other (Fuzzy) Description Logics as well. | |
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Internacional
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Si |
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ISBN
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Tipo de Tesis
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Master |
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Calificación
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Sobresaliente cum laude |
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Fecha
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22/06/2008 |