Probabilistic logic programming: Difference between revisions

Revision as of 12:27, 25 October 2023

Revision as of 12:39, 25 October 2023

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{{Programming paradigms}}

'''Probabilistic logic programming''' is a [[programming paradigm]] that combines [[logic programming]] with probabilities.

Most approaches to probabilistic logic programming are based on the distribution semantics,<ref>{{Citation |last=Riguzzi |first=Fabrizio |title=A survey of probabilistic logic programming |date=2018-09-01 |url=http://dx.doi.org/10.1145/3191315.3191319 |work=Declarative Logic Programming: Theory, Systems, and Applications |pages=185–228 |access-date=2023-10-25 |publisher=ACM |last2=Swift |first2=Theresa}}</ref> with the main exception of [[Stochastic Logic Programs]].

Its origins lie in the distribution

== Distribution semantics ==

== Languages ==

== Inference ==

== Learning ==

== Applications ==

== See also ==

* [[Probabilistic database]]

* [[Statistical relational learning]]

{{Draft categories|[[Category:Programming paradigms]]