Podrobná bibliografie
| Název: |
Probabilistic (logic) programming concepts. |
| Autoři: |
De Raedt, Luc, Kimmig, Angelika |
| Zdroj: |
Machine Learning; Jul2015, Vol. 100 Issue 1, p5-47, 43p |
| Témata: |
LOGIC programming, PROBABILITY theory, PROGRAMMING language semantics, SYNTAX in programming languages, PROGRAMMING languages |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
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