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Titlebook: Scalable Uncertainty Management; 5th International Co Salem Benferhat,John Grant Conference proceedings 2011 Springer-Verlag GmbH Berlin He

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Logic Programming and Uncertainty paper we give an overview of such languages and the kind of uncertainty they can express and reason with. Among those, we slightly elaborate on the language P-log that not only accommodates probabilistic reasoning, but also respects causality and distinguishes observational and action updates.
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Argumentation Frameworks with Necessitiess) and AFNs. We introduce then a further generalization of AFNs that extends the necessity relation to deal with sets of arguments. We give a natural adaptation of the acceptability semantics to this new context and show that the generalized frameworks allow to encode arbitrary logic programs.
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Causality, Responsibility, and Blame: A Structural-Model Approacheview the Halpern-Pearl definition of causality-what it means that . is a cause of .–and show how it handles well some standard problems of causality. This definition is based on what are called ., which are ways of describing the effects of interventions. The definition (like most in the literature
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Fuzzy Logic, Annotation Domains and Semantic Web LanguagesSemantic Web Languages such a RDF/RDFS, OWL 2 and RIF and discuss some implementation related issues. We further show to which extend we may generalise them to so-called annotation domains, that cover also e.g. temporal, provenance and trust extensions.
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