Probabilistic Constraints for Reliability Problems

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Reliability quantifies the ability of a system to perform its required function under stated conditions. The reliability of a decision is usually represented as the probability of an adequate functioning of the system where both the decision and uncontrollable variables are subject to uncertainty. In this paper we extend previous work on probabilistic constraint programming to compute such reliability, assuming probability distributions for the uncertain values. Usually this computation is very hard and requires a number of approximations, thus the computed value may be far from the exact one. Traditional methods do not provide any guarantees with respect to correctness of the results provided. We guarantee the computation of safe bounds for the reliability of a decision, which is of major relevance for problems dealing with non-linear constraints.
Original languageUnknown
Title of host publicationProceedings of the 2010 ACM Symposium on Applied Computing
PublisherACM - Association for Computing Machinery
ISBN (Print)978-1-60558-639-7
Publication statusPublished - 1 Jan 2010
EventSymposium on Applied Computing -
Duration: 1 Jan 2010 → …


ConferenceSymposium on Applied Computing
Period1/01/10 → …

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