On the Implementation of the Probabilistic Logic Programming Language ProbLog

Details On the Implementation of the Probabilistic Logic Programming Language ProbLog On the Implementation of the Probabilistic Logic Programming Language ProbLog

2010-06-23

arxiv.org/abs/1006.4442v1

Theory and Practice of Logic Programming, 11, 235-262, 2011

Computer Science

Programming Languages

28 pages; To appear in Theory and Practice of Logic Programming (TPLP)

Scientific paper

10.1017/S1471068410000566

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.

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