Lifted Variable Elimination for Probabilistic Logic Programming

• Type: Article in International Scientific Journal
• Date: 2014

Authors

Elena Bellodi (Author) Other; Evelina Lamma (Author) Other; Fabrizio Riguzzi (Author) Other; Vitor Santos Costa (Author) FCUP; Riccardo Zese (Author) Other

Journal

Title: Theory and Practice of Logic Programming

Vol. 14

Pages: 681-695

ISSN: 1471-0684

Publisher: Cambridge University Press

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 14 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-009-PQZ

DOI: 10.1017/s1471068414000283

Abstract (EN): Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances. Even if various authors have underlined its importance for probabilistic logic programming (PLP), lifted inference has been applied up to now only to relational languages outside of logic programming. In this paper we adapt Generalized Counting First Order Variable Elimination (GC-FOVE) to the problem of computing the probability of queries to probabilistic logic programs under the distribution semantics. In particular, we extend the Prolog Factor Language (PFL) to include two new types of factors that are needed for representing ProbLog programs. These factors take into account the existing causal independence relationships among random variables and are managed by the extension to variable elimination proposed by Zhang and Poole for dealing with convergent variables and heterogeneous factors. Two new operators are added to GC-FOVE for treating heterogeneous factors. The resulting algorithm, called LP2 for Lifted Probabilistic Logic Programming, has been implemented by modifying the PFL implementation of GC-FOVE and tested on three benchmarks for lifted inference. A comparison with PITA and ProbLog2 shows the potential of the approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15