Uncertainty in Artificial Intelligence
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A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge
Carlos Chesnevar, Guillermo Simari, Teresa Alsinet, Lluis Godo
Abstract:
Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible argumentation formalism based on an extension of logic programming. Although DeLP has been successfully integrated in a number of different real-world applications, DeLP cannot deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper introduces P-DeLP, a new logic programming language that extends original DeLP capabilities for qualitative reasoning by incorporating the treatment of possibilistic uncertainty and fuzzy knowledge. Such features will be formalized on the basis of PGL, a possibilistic logic based on Godel fuzzy logic.
Keywords: null
Pages: 76-84
PS Link:
PDF Link: /papers/04/p76-chesnevar.pdf
BibTex:
@INPROCEEDINGS{Chesnevar04,
AUTHOR = "Carlos Chesnevar and Guillermo Simari and Teresa Alsinet and Lluis Godo",
TITLE = "A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge",
BOOKTITLE = "Proceedings of the Twentieth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-04)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2004",
PAGES = "76--84"
}


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