Uncertainty in Artificial Intelligence
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A Principled Analysis of Merging Operations in Possibilistic Logic
Salem Benferhat, Didier Dubois, Souhila Kaci, Henri Prade
Abstract:
Possibilistic logic offers a qualitative framework for representing pieces of information associated with levels of uncertainty of priority. The fusion of multiple sources information is discussed in this setting. Different classes of merging operators are considered including conjunctive, disjunctive, reinforcement, adaptive and averaging operators. Then we propose to analyse these classes in terms of postulates. This is done by first extending the postulate for merging classical bases to the case where priorites are avaialbe.
Keywords:
Pages: 24-31
PS Link:
PDF Link: /papers/00/p24-benferhat.pdf
BibTex:
@INPROCEEDINGS{Benferhat00,
AUTHOR = "Salem Benferhat and Didier Dubois and Souhila Kaci and Henri Prade",
TITLE = "A Principled Analysis of Merging Operations in Possibilistic Logic",
BOOKTITLE = "Proceedings of the Sixteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-00)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2000",
PAGES = "24--31"
}


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