Answer Set Programming (ASP) is a well-known problem-solving formalism in computational logic. Nowadays, ASP is used in many real world scenarios thanks to ASP solvers. Standard evaluation of ASP programs suffers from an intrinsic limitation, knows as Grounding Bottleneck, due to the grounding of some rules that could fit all the available memory. As a result, there exist instances of real world problems that are untractable using the standard Ground and Solve approach. In order to tackle this problem, different strategies have been proposed. Among them we focus on a recent approach based on compilation of problematic constraints as propagators, which revealed to be very promising but is currently limited to constraints without aggregates. Since aggregates are widely used in ASP, in this paper we extend such an approach also to constraints containing aggregates. Good results, that proof the effectiveness of the proposed approach, have been reached.
翻译:答案设置编程(ASP)是计算逻辑中众所周知的解决问题的形式主义。如今,由于ASP的解决者,ASP被用于许多真实的世界情景。对ASP方案的标准评价存在内在的限制,由于某些规则的基础可以适合所有可用的记忆,被称为“地面瓶颈”。因此,存在一些使用标准“地面”和“溶解”方法无法解决的真实世界问题。为了解决这一问题,提出了不同的战略。其中我们侧重于最近采用的方法,即汇集成问题的制约因素,作为宣传者,这些制约因素显示很有希望,但目前仅限于没有综合的制约因素。由于综合数据在ASP中被广泛使用,我们在本文中也将这种方法扩大到包含总数据的限制。很好的结果是,证明拟议方法的有效性已经实现。