When we want to compute the probability of a query from a Probabilistic Answer Set Program, some parts of a program may not influence the probability of a query, but they impact on the size of the grounding. Identifying and removing them is crucial to speed up the computation. Algorithms for SLG resolution offer the possibility of returning the residual program which can be used for computing answer sets for normal programs that do have a total well-founded model. The residual program does not contain the parts of the program that do not influence the probability. In this paper, we propose to exploit the residual program for performing inference. Empirical results on graph datasets show that the approach leads to significantly faster inference.

翻译：在计算概率答案集程序中查询的概率时，程序的某些部分可能不影响查询概率，但会影响基础化规模。识别并移除这些部分对加速计算至关重要。SLG消解算法能够返回残差程序，该程序可用于计算具有完全良基模型的常规程序的答案集。残差程序不包含那些不影响概率的程序部分。本文提出利用残差程序进行概率推理。在图数据集上的实验结果表明，该方法能显著提升推理速度。