On the implementation of the probabilistic logic programming language ProbLog
Top Cited Papers
Open Access
- 27 January 2011
- journal article
- research article
- Published by Cambridge University Press (CUP) in Theory and Practice of Logic Programming
- Vol. 11 (2-3), 235-262
- https://doi.org/10.1017/s1471068410000566
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.Keywords
This publication has 18 references indexed in Scilit:
- On the Efficient Execution of ProbLog ProgramsPublished by Springer Science and Business Media LLC ,2008
- Basic Principles of Learning Bayesian Logic ProgramsLecture Notes in Computer Science, 2008
- Compressing probabilistic Prolog programsMachine Learning, 2007
- Logic Programs with Annotated DisjunctionsLecture Notes in Computer Science, 2004
- Efficient access mechanisms for tabled logic programsThe Journal of Logic Programming, 1999
- Probabilistic Horn abduction and Bayesian networksArtificial Intelligence, 1993
- Associative-commutative discrimination netsLecture Notes in Computer Science, 1993
- Graph-Based Algorithms for Boolean Function ManipulationIEEE Transactions on Computers, 1986
- The Complexity of Enumeration and Reliability ProblemsSIAM Journal on Computing, 1979
- Trie memoryCommunications of the ACM, 1960