DNF Sampling for ProbLog Inference

Details DNF Sampling for ProbLog Inference DNF Sampling for ProbLog Inference

2010-09-20

arxiv.org/abs/1009.3798v2

Proceedings of CICLOPS-WLPE 2010

Computer Science

Logic in Computer Science

Online proceedings of the Joint Workshop on Implementation of Constraint Logic Programming Systems and Logic-based Methods in

Scientific paper

Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduction to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computationally 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 probabilistic logic systems. The paper also presents an experimental comparison with another sampling based inference method previously introduced for ProbLog.

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