Inference and learning in probabilistic logic programs using weighted Boolean formulas

Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. This paper investigates how classical inference and learning tasks known from the graphical model community can be tackled for probabilistic logic programs. Several such tasks, such as comput...

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Bibliographic Details

Published in:	Theory and practice of logic programming Vol. 15; no. 3; pp. 358 - 401
Main Authors:	FIERENS, DAAN, VAN DEN BROECK, GUY, RENKENS, JORIS, SHTERIONOV, DIMITAR, GUTMANN, BERND, THON, INGO, JANSSENS, GERDA, DE RAEDT, LUC
Format:	Journal Article
Language:	English
Published:	Cambridge, UK Cambridge University Press 01.05.2015
Subjects:	Algorithms Inference Learning Logic programming Mathematical models Parameter learn-ing Probabilistic inference Probabilistic logic programming Probabilistic methods Probability theory Regular Papers Tasks probabilistic inference parameter learning probabilistic logic programming
ISSN:	1471-0684, 1475-3081, 1475-3081
Online Access:	Get full text
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