ProbLog is a probabilistic logic programming language that extends Prolog with probabilities.
[1][2][3] It minimally extends Prolog by adding the notion of a probabilistic fact, which combines the idea of logical atoms and random variables.
Similarly to Prolog, ProbLog can query an atom.
While Prolog returns the truth value of the queried atom, ProbLog returns the probability of it being true.
A probabilistic fact is a pair
, called the head, and a finite set of
ProbLog programs consist of a set of probabilistic facts
Using the distribution semantics, a probability distribution is defined over the two-valued well-founded models of the atoms in the program.
where the product runs over all the literals in the model
the distribution semantics defines a probability for the query
ProbLog supports multiple tasks: ProbLog can for example be used to calculate the probability of getting wet given the probabilities for rain and the probabilities that someone brings an umbrella as follows: The last rule before the query states that someone gets wet if it rains and no umbrella was brought.
When ProbLog is asked to solve the "probabilistic inference" task, the query asks for the probability to stay dry on a weekend day.
When solving the "most probable explanation" task, ProbLog will return the most likely reason for staying dry, i.e. because it is not raining or because the person has an umbrella.
[4] and as a stand-alone Python framework (ProbLog 2)[5] The source code of ProbLog 2 is licensed under Apache License, Version 2.0 and available on GitHub.
[6] The ProbLog language has also been implemented as part of the cplint probabilistic logic programming package for SWI-Prolog, YAP and XSB.
[7] ProbLog has been extended or used as inspiration for several different variants, including: