caa a22 4500 605478163 CHVBK 20210128100404.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s10994-015-5494-z doi (NATIONALLICENCE)springer-10.1007/s10994-015-5494-z Probabilistic (logic) programming concepts [Elektronische Daten] [Luc De Raedt, Angelika Kimmig] A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability distributions. Each of these languages employs its own probabilistic primitives, and comes with a particular syntax, semantics and inference procedure. This makes it hard to understand the underlying programming concepts and appreciate the differences between the different languages. To obtain a better understanding of probabilistic programming, we identify a number of core programming concepts underlying the primitives used by various probabilistic languages, discuss the execution mechanisms that they require and use these to position and survey state-of-the-art probabilistic languages and their implementation. While doing so, we focus on probabilistic extensions of logic programming languages such as Prolog, which have been considered for over 20 years. The Author(s), 2015 Probabilistic programming languages nationallicence Probabilistic logic programming nationallicence Statistical relational learning nationallicence Inference in probabilistic languages nationallicence De Raedt Luc Department of Computer Science, KU Leuven, Celestijnenlaan 200A, Bus 2402, 3001, Heverlee, Belgium aut Kimmig Angelika Department of Computer Science, KU Leuven, Celestijnenlaan 200A, Bus 2402, 3001, Heverlee, Belgium aut Machine Learning Springer US; http://www.springer-ny.com 100/1(2015-07-01), 5-47 0885-6125 100:1<5 2015 100 10994 https://doi.org/10.1007/s10994-015-5494-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10994-015-5494-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- De Raedt Luc Department of Computer Science, KU Leuven, Celestijnenlaan 200A, Bus 2402, 3001, Heverlee, Belgium aut NATIONALLICENCE 700 1- Kimmig Angelika Department of Computer Science, KU Leuven, Celestijnenlaan 200A, Bus 2402, 3001, Heverlee, Belgium aut NATIONALLICENCE 773 0- Machine Learning Springer US; http://www.springer-ny.com 100/1(2015-07-01), 5-47 0885-6125 100:1<5 2015 100 10994