Probabilistic (logic) programming concepts

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 particu...

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Bibliographic Details
Published in:Machine learning Vol. 100; no. 1; pp. 5 - 47
Main Authors: De Raedt, Luc, Kimmig, Angelika
Format: Journal Article
Language:English
Published: New York Springer US 01.07.2015
Springer Nature B.V
Subjects:
Artificial Intelligence
Computer Science
Control
Inference in probabilistic languages
Logic programming
Mechatronics
Natural Language Processing (NLP)
Probabilistic logic programming
Probabilistic methods
Probabilistic programming languages
Probability theory
Programming
Programming languages
Prolog
Prolog (programming language)
Robotics
Semantics
Simulation and Modeling
Statistical relational learning
Inference in probabilistic languages
Statistical relational learning
Probabilistic programming languages
Probabilistic logic programming
ISSN:0885-6125, 1573-0565, 1573-0565
Online Access:Get full text
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Summary: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.
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ISSN:0885-6125
1573-0565
1573-0565
DOI:10.1007/s10994-015-5494-z