Bayesian knowledge bases (BKBs) are a gen eralization of Bayes networks and weighted proof graphs (WAODAGs), that allow cycles in the causal graph. Reasoning in BKBs re quires finding the most probable inferences consistent with the evidence. The cost sharing heuristic for finding least-cost ex planations in WAODAGs was presented and shown to be effective by Charniak and Hu sain. However, the cycles in BKBs would make the definition of cost-sharing cyclic as well, if applied directly to BKBs. By treat ing the defining equations of cost-sharing as a system of equations, one can properly de fine an admissible cost-sharing heuristic for BKBs. Empirical evaluation shows that cost sharing improves performance significantly when applied to BKBs.
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