Uncertainty in Artificial Intelligence
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Argumentative inference in uncertain and inconsistent knowledge bases
Salem Benferhat, Didier Dubois, Henri Prade
Abstract:
This paper presents and discusses several methods for reasoning from inconsistent knowledge bases. A so-called argumentative-consequence relation taking into account the existence of consistent arguments in favor of a conclusion and the absence of consistent arguments in favor of its contrary, is particularly investigated. Flat knowledge bases, i.e. without any priority between their elements, as well as prioritized ones where some elements are considered as more strongly entrenched than others are studied under different consequence relations. Lastly a paraconsistent-like treatment of prioritized knowledge bases is proposed, where both the level of entrenchment and the level of paraconsistency attached to a formula are propagated. The priority levels are handled in the framework of possibility theory.
Keywords:
Pages: 411-419
PS Link:
PDF Link: /papers/93/p411-benferhat.pdf
BibTex:
@INPROCEEDINGS{Benferhat93,
AUTHOR = "Salem Benferhat and Didier Dubois and Henri Prade",
TITLE = "Argumentative inference in uncertain and inconsistent knowledge bases",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "411--419"
}


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