On the Efficient Execution of ProbLog Programs

Angelika Kimmig, Vítor Santos Costa, Ricardo Rocha, Bart Demoen and Luc De Raedt

December 2008

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Abstract

The past few years have seen a surge of interest in the field of probabilistic logic learning or 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 mutually independent probabilities that they 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

@InProceedings{kimmig-iclp08,
  author =    {A. Kimmig and V. Santos Costa and R. Rocha and B. Demoen and L. De Raedt},
  title =     {{On the Efficient Execution of ProbLog Programs}},
  booktitle = {Proceedings of the 24th International Conference on Logic Programming (ICLP 2008)},
  pages =     {175--189},
  number =    {5366},
  series =    {LNCS},
  publisher = {Springer},
  editor =    {M. Garcia de la Banda and E. Pontelli},
  month =     {December},
  year =      {2008},
  address =   {Udine, Italy},
}

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