Artificial Intelligence
Readings in model-based diagnosis
Readings in model-based diagnosis
Decision-theoretic troubleshooting
Communications of the ACM
A comparison of decision alaysis and expert rules for sequential diagnosis
UAI '88 Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence
Exploiting system hierarchy to compute repair plans in probabilistic model-based diagnosis
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Printer troubleshooting using Bayesian networks
IEA/AIE '00 Proceedings of the 13th international conference on Industrial and engineering applications of artificial intelligence and expert systems: Intelligent problem solving: methodologies and approaches
The SACSO methodology for troubleshooting complex systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Efficient interpretation policies
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Extensions of decision-theoretic troubleshooting: cost clusters and precedence constraints
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
A knowledge acquisition tool for Bayesian-network troubleshooters
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Modeling failure priors and persistence in model-based diagnosis
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Exploiting system hierarchy to compute repair plans in probabilistic model-based diagnosis
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Decision-theoretic troubleshooting: Hardness of approximation
International Journal of Approximate Reasoning
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The goal of diagnosis is to compute good repair strategies in response to anomalous system behavior. In a decision theoretic framework, a good repair strategy has low expected cost. In a general formulation of the problem, the computation of the optimal (lowest expected cost) repair strategy for a system with multiple faults is intractable. In this paper, we consider an interesting and natural restriction on the behavior of the system being diagnosed: (a) the system exhibits faulty behavior if and only if one or more components is malfunctioning. (b) The failures of the system components are independent. Given this restriction on system behavior, we develop a polynomial time algorithm for computing the optimal repair strategy. We then go on to introduce a system hierarchy and the notion of inspecting (testing) components before repair. We develop a linear time algorithm for computing an optimal repair strategy for the hierarchical system which includes both repair and inspection.