By the same authors

CLP(BN ): constraint logic programming for probabilistic knowledge

Research output: Chapter in Book/Report/Conference proceedingChapter



Publication details

Title of host publicationProbabilistic Inductive Logic Programming
DatePublished - 2008
Number of pages32
Place of PublicationBerlin
EditorsLuc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton
Original languageEnglish
ISBN (Print)978-3-540-78651-1

Publication series

NameLecture Notes in Artificial Intelligence


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

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