Graded logics: A framework for uncertain and defeasible knowledge

  • Philippe Chatalic
  • Christine Froidevaux
Communications Logic For Artificial Intelligence
Part of the Lecture Notes in Computer Science book series (LNCS, volume 542)


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.


Knowledge Representation Defeasible Reasoning Uncertainty Graded Logic Default Logic 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Philippe Chatalic
    • 1
  • Christine Froidevaux
    • 1
  1. 1.Laboratoire de Recherche en Informatique - UA CNRS 410 Bat 490Université Paris-SudOrsay CedexFrance

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