DNF sampling for ProbLog inference

Dimitar S. Shterionov, Angelika Kimmig, Theofrastos Mantadelis, Gerda Janssens

Research output: Contribution to conferencePaperOther research output

2 Citations (Scopus)

Abstract

Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduc- tion to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computation- ally hard. In this work we introduce a new approximation method for ProbLog inference which exploits the DNF to focus sampling. While this DNF sampling technique has been applied to a variety of tasks before, to the best of our knowledge it has not been used for inference in probabilis- tic logic systems. The paper also presents an experimental comparison with another sampling based inference method previously introduced for ProbLog.

Original languageEnglish
Number of pages1
Publication statusPublished - 2010
Externally publishedYes
Event26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010 - Edinburgh, Scotland, United Kingdom
Duration: 15 Jul 201015 Jul 2010

Conference

Conference26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010
CountryUnited Kingdom
CityEdinburgh, Scotland
Period15/07/1015/07/10

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  • Cite this

    Shterionov, D. S., Kimmig, A., Mantadelis, T., & Janssens, G. (2010). DNF sampling for ProbLog inference. Paper presented at 26th International Conference on Logic Programming, ICLP 2010 - Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in Programming Environments - CICLOPS-WLPE 2010, Edinburgh, Scotland, United Kingdom.