Uncertainty in Artificial Intelligence
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A New Algorithm for Finding MAP Assignments to Belief Network
Solomon Shimony, Eugene Charniak
Abstract:
We present a new algorithm for finding maximum a-posterior) (MAP) assignments of values to belief networks. The belief network is compiled into a network consisting only of nodes with boolean (i.e. only 0 or 1) conditional probabilities. The MAP assignment is then found using a best-first search on the resulting network. We argue that, as one would anticipate, the algorithm is exponential for the general case, but only linear in the size of the network for poly trees.
Keywords: null
Pages: 185-193
PS Link:
PDF Link: /papers/90/p185-shimony.pdf
BibTex:
@INPROCEEDINGS{Shimony90,
AUTHOR = "Solomon Shimony and Eugene Charniak",
TITLE = "A New Algorithm for Finding MAP Assignments to Belief Network",
BOOKTITLE = "Uncertainty in Artificial Intelligence 6 Annual Conference on Uncertainty in Artificial Intelligence (UAI-90)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1990",
PAGES = "185--193"
}


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