Tabling for contextual abduction in logic programming has been introduced as a means to store previously obtained abductive solutions in one context to be reused in another context. This paper identifies a number of issues in the existing implementations of tabling in contextual abduction and aims to mitigate the issues. We propose a new program transformation for integrity constraints to deal with their proper application for filtering solutions while also reducing the table memory usage. We further optimize the table memory usage by selectively picking predicates to table and by pragmatically simplifying the representation of the problem. The evaluation of our proposed approach, on both artificial and real world problems, shows that they improve the scalability of tabled abduction compared to previous implementations.
翻译:在逻辑编程中将背景绑架列为列表,作为将先前获得的绑架性解决办法储存在一种情况下,再用于另一种情况下的一种手段,本文件确定了目前对背景绑架进行列表的一些问题,并旨在缓解这些问题。我们建议对完整性限制进行新的方案改造,以适当应用过滤解决方案,同时减少表格记忆的使用。我们进一步优化表格记忆使用,有选择地从桌面上选取上游数据,并务实地简化这一问题的表述方式。对关于人为和现实世界问题的拟议方法的评估表明,与以往的实施相比,这些方法提高了现案绑架的可扩展性。