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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Veröffentlicht in:	Theory and practice of logic programming Jg. 15; H. 3; S. 358 - 401
Hauptverfasser:	FIERENS, DAAN, VAN DEN BROECK, GUY, RENKENS, JORIS, SHTERIONOV, DIMITAR, GUTMANN, BERND, THON, INGO, JANSSENS, GERDA, DE RAEDT, LUC
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cambridge, UK Cambridge University Press 01.05.2015
Schlagworte:	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-Zugang:	Volltext
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