Abstract
Real-life management decisions are usually made in uncertain environments, and decision support systems that ignore this uncertainty are unlikely to provide realistic guidance. We show that previous approaches fail to provide appropriate support for reasoning about reliability under uncertainty. We propose a new framework that addresses this issue by allowing logical dependencies between constraints. Reliability is then defined in terms of key constraints called “events”, which are related to other constraints via these dependencies. We illustrate our approach on two problems, contrast it with existing frameworks, and discuss future developments.
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© 2006 Springer-Verlag Berlin Heidelberg
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Tarim, S.A., Hnich, B., Prestwich, S.D. (2006). Event-Driven Probabilistic Constraint Programming. In: Beck, J.C., Smith, B.M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2006. Lecture Notes in Computer Science, vol 3990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11757375_17
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DOI: https://doi.org/10.1007/11757375_17
Publisher Name: Springer, Berlin, Heidelberg
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