Abstract
We propose a framework for dealing with probabilistic uncertainty in constraint satisfaction problems, associating with each constraint the probability that it is a part of the real problem (the latter being only partially known). The probability degrees on the relevance of the constraints enable us to define, for each instanciation, the probability that it is a solution of the real problem. We briefly give a methodology for the search of the best solution (maximizing this probability).
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© 1993 Springer-Verlag Berlin Heidelberg
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Fargier, H., Lang, J. (1993). Uncertainty in constraint satisfaction problems: A probabilistic approach. In: Clarke, M., Kruse, R., Moral, S. (eds) Symbolic and Quantitative Approaches to Reasoning and Uncertainty. ECSQARU 1993. Lecture Notes in Computer Science, vol 747. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028188
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DOI: https://doi.org/10.1007/BFb0028188
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