On the implementation of the probabilistic logic programming language ProbLog

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Angelika Kimmig (Author) Other; Bart Demoen (Author) Other; Luc De Raedt (Author) Other; Vitor Santos Costa (Author) FCUP; Ricardo Rocha (Author) FCUP

Journal

Title: Theory and Practice of Logic Programming

Vol. 11

Pages: 235-262

ISSN: 1471-0684

Publisher: Cambridge University Press

Indexing

ISI Web of Knowledge - 86 Citations

Scopus - 123 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-002-V1J

DOI: 10.1017/s1471068410000566

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 28