Uncertainty in Artificial Intelligence
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Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning
Michael Horsch, Bill Havens
Abstract:
We document a connection between constraint reasoning and probabilistic reasoning. We present an algorithm, called {em probabilistic arc consistency}, which is both a generalization of a well known algorithm for arc consistency used in constraint reasoning, and a specialization of the belief updating algorithm for singly-connected networks. Our algorithm is exact for singly- connected constraint problems, but can work well as an approximation for arbitrary problems. We briefly discuss some empirical results, and related methods.
Keywords: constraint satisfaction, arc consistency, probabilistic reasoning
Pages: 282-290
PS Link: http://www.cs.usask.ca/faculty/horsch/publications/u238.ps.gz
PDF Link: /papers/00/p282-horsch.pdf
BibTex:
@INPROCEEDINGS{Horsch00,
AUTHOR = "Michael Horsch and Bill Havens",
TITLE = "Probabilistic Arc Consistency: A Connection between Constraint Reasoning and Probabilistic Reasoning",
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 = "282--290"
}


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