论文标题
对上下文绑架进行优化
Tabling Optimization for Contextual Abduction
论文作者
论文摘要
已引入将逻辑编程绑架的上下文绑架进行介绍，以作为存储先前获得的绑架解决方案的一种手段，以便在另一种上下文中重复使用。本文在上下文绑架中确定了现有的表格实施实现中的许多问题，并旨在减轻问题。我们为完整性约束提出了一个新的程序转换，以处理其适当的过滤解决方案的应用，同时还减少了表存储器的使用情况。我们通过选择性地将谓词选择到表和务实地简化了问题的表示，从而进一步优化了表存储器的使用情况。对人工和现实世界问题的评估，我们提出的方法表明，与以前的实施相比，它们提高了绑架的可扩展性。
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.
