Uncertainty in Artificial Intelligence
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Conditional Independence in Uncertainty Theories
Prakash Shenoy
Abstract:
This paper introduces the notions of independence and conditional independence in valuation-based systems (VBS). VBS is an axiomatic framework capable of representing many different uncertainty calculi. We define independence and conditional independence in terms of factorization of the joint valuation. The definitions of independence and conditional independence in VBS generalize the corresponding definitions in probability theory. Our definitions apply not only to probability theory, but also to Dempster-Shafer's belief-function theory, Spohn's epistemic-belief theory, and Zadeh's possibility theory. In fact, they apply to any uncertainty calculi that fit in the framework of valuation-based systems.
Keywords:
Pages: 284-291
PS Link:
PDF Link: /papers/92/p284-shenoy.pdf
BibTex:
@INPROCEEDINGS{Shenoy92,
AUTHOR = "Prakash Shenoy ",
TITLE = "Conditional Independence in Uncertainty Theories",
BOOKTITLE = "Proceedings of the Eighth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-92)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1992",
PAGES = "284--291"
}


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