A New Algorithm for Finding MAP Assignments to Belief Network
Solomon Shimony, Eugene Charniak
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.
PDF Link: /papers/90/p185-shimony.pdf
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"