论文标题
通过量身定制的简化，对地面逻辑程序的增量维护
Incremental maintenance of overgrounded logic programs with tailored simplifications
论文作者
论文摘要
在许多应用方案（例如流推理和事件处理）中，需要重复执行推理任务。在这种情况下使用答案集编程时，可以避免迭代生成地面程序，从而在计算时间方面取得了巨大的回报。但是，这可能需要额外的内存和/或手动在手头声明的知识库中添加操作指令。我们介绍了一种新的策略，以生成一系列单调增长的命题计划。提议的带裁缝（OPTS）的地面程序可以与连续输入结合使用并重复使用。关于较早的方法，我们量身定制的简化技术减少了实例化程序的大小。维护的OPT慢慢地增长了从迭代到另一个迭代，而更新成本降低，尤其是在以后的迭代中。在本文中，我们正式引入了量身定制的嵌入，这是一个基于OPTS的理论基础的等价基础程序的家族，我们描述了它们的特性。然后，我们说明了OPT UPDATE算法并报告有关我们的实现及其性能的报告。本文在逻辑编程（TPLP）的理论和实践中正在考虑。
The repeated execution of reasoning tasks is desirable in many applicative scenarios, such as stream reasoning and event processing. When using answer set programming in such contexts, one can avoid the iterative generation of ground programs thus achieving a significant payoff in terms of computing time. However, this may require some additional amount of memory and/or the manual addition of operational directives in the declarative knowledge base at hand. We introduce a new strategy for generating series of monotonically growing propositional programs. The proposed overgrounded programs with tailoring (OPTs) can be updated and reused in combination with consecutive inputs. With respect to earlier approaches, our tailored simplification technique reduces the size of instantiated programs. A maintained OPT slowly grows in size from an iteration to another while the update cost decreases, especially in later iterations. In this paper we formally introduce tailored embeddings, a family of equivalence-preserving ground programs which are at the theoretical basis of OPTs and we describe their properties. We then illustrate an OPT update algorithm and report about our implementation and its performance. This paper is under consideration in Theory and Practice of Logic Programming (TPLP).
