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A PRM is usually developed with a set of algorithms for reducing, inference about and discovery of concerned distributions, which are embedded into the corresponding PRPL.
=== Probabilistic logic programming ===
{{Main|Probabilistic logic programming}}
Probabilistic logic programming is a [[programming paradigm]] that extends [[logic programming]] with probabilities.
Most approaches to probabilistic logic programming are based on the ''distribution semantics,'' which splits a program into a set of probabilistic facts and a logic program. It defines a probability distribution on interpretations of the [[Herbrand structure|Herbrand universe]] of the program.<ref>{{Cite journal |last=De Raedt |first=Luc |last2=Kimmig |first2=Angelika |date=2015-07-01 |title=Probabilistic (logic) programming concepts |url=https://doi.org/10.1007/s10994-015-5494-z |journal=Machine Learning |language=en |volume=100 |issue=1 |pages=5–47 |doi=10.1007/s10994-015-5494-z |issn=1573-0565}}</ref>
=== List of probabilistic programming languages ===
This list summarises the variety of PPLs that are currently available, and clarifies their origins.{{Overly detailed|date=October 2019}}
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