  Cutset conditioning and clique-tree propagation are two popular methods for
performing exact probabilistic inference in Bayesian belief networks. Cutset
conditioning is based on decomposition of a subset of network nodes, whereas
clique-tree propagation depends on aggregation of nodes. We describe a means to
combine cutset conditioning and clique- tree propagation in an approach called
aggregation after decomposition (AD). We discuss the application of the AD
method in the Pathfinder system, a medical expert system that offers assistance
with diagnosis in hematopathology.
