CLP(BN ): constraint logic programming for probabilistic knowledge

V. Santos Costa, D. Page, J. Cussens

Research output: Chapter in Book/Report/Conference proceedingChapter


In Datalog, missing values are represented by Skolem constants. More generally, in logic programming missing values, or existentially quantified variables, are represented by terms built from Skolem functors. The CLP(BN) language represents the joint probability distribution over missing values in a database or logic program by using constraints to represent Skolem functions. Algorithms from inductive logic programming (ILP) can be used with only minor modification to learn CLP(BN) programs. An implementation of CLP(BN) is publicly available as part of YAP Prolog at
Original languageEnglish
Title of host publicationProbabilistic Inductive Logic Programming
Subtitle of host publicationTheory and Applications
EditorsLuc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton
Place of PublicationBerlin
Number of pages32
ISBN (Print)978-3-540-78651-1
Publication statusPublished - 2008

Publication series

NameLecture Notes in Artificial Intelligence

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