An Algorithm for Computing Probabilistic Propositions
arXiv:1304.2754
Abstract
A method for computing probabilistic propositions is presented. It assumes the availability of a single external routine for computing the probability of one instantiated variable, given a conjunction of other instantiated variables. In particular, the method allows belief network algorithms to calculate general probabilistic propositions over nodes in the network. Although in the worst case the time complexity of the method is exponential in the size of a query, it is polynomial in the size of a number of common types of queries.
Appears in Proceedings of the Third Conference on Uncertainty in Artificial Intelligence (UAI1987)