Better Safe than Sorry - Optimal Troubleshooting through A* Search with Efficiency-based Pruning

Decision theoretic troubleshooting combines Bayesian networks and cost estimates to obtain optimal or near optimal decisions in domains with inherent uncertainty. In this paper we use the well-known A* algorithm extended with pruning based on the efficiency of actions for finding optimal solutions in troubleshooting. In particular, we focus on models with dependent actions.