# Inference in Probabilistic Logic Programs using Lifted Explanations

## Arun Nampally, C. R. Ramakrishnan

### Abstract

In this paper, we consider the problem of lifted inference in the
context of Prism-like probabilistic logic programming languages.
Traditional inference in such languages involves the construction of
an explanation graph for the query that treats each instance of a
random variable separately. For many programs and queries, we
observe that explanations can be summarized into substantially more
compact structures introduced in this paper, called “lifted explanation graphs”.
In contrast to existing lifted inference techniques, our
method for constructing lifted explanations naturally generalizes
existing methods for constructing explanation graphs. To compute
probability of query answers, we solve recurrences generated from
the lifted graphs. We show examples where the use of our technique
reduces the asymptotic complexity of inference.

paper.pdf

Last modified: Tue Aug 9 01:31:48 EDT 2016