Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
A comparison of decision alaysis and expert rules for sequential diagnosis
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
The SACSO methodology for troubleshooting complex systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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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.