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- W1533036623 abstract "We argue that the clp(X) framework is a suitable vehicle for extending logic programming (LP) with probabilistic reasoning. This paper presents such a generic framework, clp(pdf(Y)), and proposes two promising instances. The first provides a seamless integration of Bayesian Networks, while the second defines distributions over variables and employs conditional constraints over predicates. The generic methodology is based on attaching probability distributions over finite domains. We illustrate computational benefits of this approach by comparing program performances with a clp(fd) program on a cryptographic problem." @default.
- W1533036623 created "2016-06-24" @default.
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- W1533036623 date "2003-01-01" @default.
- W1533036623 modified "2023-09-27" @default.
- W1533036623 title "clp(pdf(y)): Constraints for Probabilistic Reasoning in Logic Programming" @default.
- W1533036623 cites W1480830699 @default.
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- W1533036623 doi "https://doi.org/10.1007/978-3-540-45193-8_53" @default.
- W1533036623 hasPublicationYear "2003" @default.
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