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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Vydáno v:	Theory and practice of logic programming Ročník 15; číslo 3; s. 358 - 401
Hlavní autoři:	FIERENS, DAAN, VAN DEN BROECK, GUY, RENKENS, JORIS, SHTERIONOV, DIMITAR, GUTMANN, BERND, THON, INGO, JANSSENS, GERDA, DE RAEDT, LUC
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 01.05.2015
Témata:	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
On-line přístup:	Získat plný text
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