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},
}

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Cambridge University Press
The Computing Research Repository (CoRR)