Abstract
Intelligent systems require the ability to reason with incomplete knowledge. This paper presents a logical framework based on a lattice structure for handling uncertainty. Formal properties of graded inference are studied extensively. We provide a semantics for graded logic and give a sound and complete axiomatization. Finally we show how the generalization of graded inference to default rules, combined with fixpoint techniques, allows for a formalization of defeasible reasoning with uncertain knowledge.
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Chatalic, P., Froidevaux, C. (1991). Graded logics: A framework for uncertain and defeasible knowledge. In: Ras, Z.W., Zemankova, M. (eds) Methodologies for Intelligent Systems. ISMIS 1991. Lecture Notes in Computer Science, vol 542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-54563-8_111
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DOI: https://doi.org/10.1007/3-540-54563-8_111
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