Inference in Polytrees with Sets of Probabilities
نویسندگان
چکیده
Inferences in directed acyclic graphs associated with probability intervals and sets of probabil ities are NP-hard, even for polytrees. We pro pose: I) an improvement on Tessem's AIR algo rithm for inferences on polytrees associated with probability intervals; 2) a new algorithm for ap proximate inferences based on local search; 3) branch-and-bound algorithms that combine the previous techniques. The first two algorithms produce complementary approximate solutions, while branch-and-bound procedures can gener ate either exact or approximate solutions. We report improvements on existing techniques for inference with probability sets and intervals, in some cases reducing computational effort by sev eral orders of magnitude.
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تاریخ انتشار 2003