Uncertainty in Artificial Intelligence
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Mixtures of Deterministic-Probabilistic Networks and their AND/OR Search Space
Rina Dechter, Robert Mateescu
Abstract:
The paper introduces mixed networks, a new framework for expressing and reasoning with probabilistic and deterministic information. The framework combines belief networks with constraint networks, defining the semantics and graphical representation. We also introduce the AND/OR search space for graphical models, and develop a new linear space search algorithm. This provides the basis for understanding the benefits of processing the constraint information separately, resulting in the pruning of the search space. When the constraint part is tractable or has a small number of solutions, using the mixed representation can be exponentially more effective than using pure belief networks which odel constraints as conditional probability tables.
Keywords: null
Pages: 120-129
PS Link:
PDF Link: /papers/04/p120-dechter.pdf
BibTex:
@INPROCEEDINGS{Dechter04,
AUTHOR = "Rina Dechter and Robert Mateescu",
TITLE = "Mixtures of Deterministic-Probabilistic Networks and their AND/OR Search Space",
BOOKTITLE = "Proceedings of the Twentieth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-04)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2004",
PAGES = "120--129"
}


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