
The Relationship between Knowledge, Belief and Certainty
We consider the relation between knowledge and certainty, where a fact i...
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NonMonotonicity in Probabilistic Reasoning
We start by defining an approach to nonmonotonic probabilistic reasonin...
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On the Relation between Kappa Calculus and Probabilistic Reasoning
We study the connection between kappa calculus and probabilistic reasoni...
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A Model for NonMonotonic Reasoning Using Dempster's Rule
Considerable attention has been given to the problem of nonmonotonic re...
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Preferential Structures for Comparative Probabilistic Reasoning
Qualitative and quantitative approaches to reasoning about uncertainty c...
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Declarative Representation of Revision Strategies
In this paper we introduce a nonmonotonic framework for belief revision ...
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A new approach for generation of generalized basic probability assignment in the evidence theory
The process of information fusion needs to deal with a large number of u...
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Syntaxbased Default Reasoning as Probabilistic Modelbased Diagnosis
We view the syntaxbased approaches to default reasoning as a modelbased diagnosis problem, where each source giving a piece of information is considered as a component. It is formalized in the ATMS framework (each source corresponds to an assumption). We assume then that all sources are independent and "fail" with a very small probability. This leads to a probability assignment on the set of candidates, or equivalently on the set of consistent environments. This probability assignment induces a DempsterShafer belief function which measures the probability that a proposition can be deduced from the evidence. This belief function can be used in several different ways to define a nonmonotonic consequence relation. We study and compare these consequence relations. The case of prioritized knowledge bases is briefly considered.
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