Algorithms in C
The complexity of one-machine batching problems
Discrete Applied Mathematics - Special issue on new frontiers in the theory and practice of combinatorial optimization: applications in manufacturing and VLSI design
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
Scheduling Algorithms
Heuristics for Two Extensions of Basic Troubleshooting
SCAI '01 Proceedings of the Seventh Scandinavian Conference on Artificial Intelligence
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 recognition of Series Parallel digraphs
STOC '79 Proceedings of the eleventh annual ACM symposium on Theory of computing
The SACSO methodology for troubleshooting complex systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Decision-theoretic troubleshooting: a framework for repair and experiment
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Decision-theoretic troubleshooting: Hardness of approximation
International Journal of Approximate Reasoning
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In decision-theoretic troubleshooting [5,2], we try to find a cost efficient repair strategy for a malfunctioning device described by a formal model. The need to schedule repair actions under uncertainty has required the researchers to use an appropriate knowledge representation formalism, often a probabilistic one. The troubleshooting problem has received considerable attention over the past two decades. Efficient solution algorithms have been found for some variants of the problem, whereas other variants have been proven NP-hard [5,2,4,17,16]. We show that two troubleshooting scenarios -- Troubleshooting with Postponed System Test [9] and Troubleshooting with Cost Clusters without Inside Information [7]--are NP-hard. Also, we define a troubleshooting scenario with precedence restrictions on the repair actions. We show that it is NP-hard in general, but polynomial under some restrictions placed on the structure of the precedence relation. In the proofs, we use results originally achieved in the field of Scheduling. Such a connection has not been made in the Troubleshooting literature so far.