On the Implementation of the Probabilistic Logic Programming Language ProbLog
Angelika Kimmig, Bart Demoen, Luc De Raedt, VĂtor Santos Costa and Ricardo Rocha
2011
Abstract
The past few years have seen a surge of interest in the field of
probabilistic logic learning and statistical relational learning. In
this endeavor, many probabilistic logics have been developed. ProbLog
is a recent probabilistic extension of Prolog motivated by the mining
of large biological networks. In ProbLog, facts can be labeled with
probabilities. These facts are treated as mutually independent random
variables that indicate whether these facts belong to a randomly
sampled program. Different kinds of queries can be posed to ProbLog
programs. We introduce algorithms that allow the efficient execution
of these queries, discuss their implementation on top of the
YAP-Prolog system, and evaluate their performance in the context of
large networks of biological entities.
Bibtex
@Article{kimmig-tplp11,
author = {A. Kimmig and B. Demoen and L. De Raedt and V. Santos Costa and R. Rocha},
title = {{On the Implementation of the Probabilistic Logic Programming Language ProbLog}},
journal = {Journal of Theory and Practice of Logic Programming},
pages = {235--262},
volume = {11},
number = {2 \& 3},
year = {2011},
}
Download Paper
PDF file
Cambridge University Press
Computing Research Repository (CoRR)