Cost-sharing in Bayesian knowledge bases

Authors:
Solomon Eyal Shimony;Carmel Domshlak;Eugene Santos
Affiliations:
Dept. of Math. and Comp. Sci., Ben Gurion University of the Negev, Beer-Sheva, Israel;Dept. of Math. and Comp. Sci., Ben Gurion University of the Negev, Beer-Sheva, Israel;Dept. of Electrical and Comp. Eng., Air Force Institute of Technology, Wright-Patterson AFB, OH
Venue:
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Year:
1997

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Abstract

Bayesian knowledge bases (BKBs) are a generalization of Bayes networks and weighted proof graphs (WAODAGs), that allow cycles in the causal graph. Reasoning in BKBs requires finding the most probable inferences consistent with the evidence. The costsharing heuristic for finding least-cost explanations in WAODAGs was presented and shown to be effective by Charniak and Husain. However, the cycles in BKBs would make the definition of cost-sharing cyclic as well, if applied directly to BKBs. By treating the defining equations of cost-sharing as a system of equations, one can properly define an admissible cost-sharing heuristic for BKBs. Empirical evaluation shows that costsharing improves performance significantly when applied to BKBs.