Declarative probabilistic logic programming in discrete-continuous domains

Over the past three decades, the logic programming paradigm has been successfully expanded to support probabilistic modeling, inference and learning. The resulting paradigm of probabilistic logic programming (PLP) and its programming languages owes much of its success to a declarative semantics, the...

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Veröffentlicht in:	Artificial intelligence Jg. 337; S. 104227
Hauptverfasser:	Zuidberg Dos Martires, Pedro, De Raedt, Luc, Kimmig, Angelika
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2024
Schlagworte:	Algebraic model counting Declarative semantics Discrete-continuous distributions Knowledge compilation Likelihood weighting Logic programming Probabilistic programming Logic programming Probabilistic programming Discrete-continuous distributions Algebraic model counting Declarative semantics Likelihood weighting Knowledge compilation
ISSN:	0004-3702, 1872-7921
Online-Zugang:	Volltext
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