稳定模型语义中的展开偏性与析取
Unfolding Partiality and Disjunctions in Stable Model Semantics
摘要：
本文研究了部分和析取稳定模型的实现方法，其中，从逻辑程序中展开析取和析取，使得正常（无析取）程序的稳定模型的实现可以用作核心推理机。展开分两步进行。首先，它表明，部分稳定的模型可以捕获的总稳定的模型，使用一个简单的线性和模块化的程序转换。因此，部分稳定模型的推理任务，可以解决使用总稳定模型的实现。分离的部分稳定模型一直缺乏实现，现在可以作为翻译处理分离的情况。其次，它表明如何总的稳定模型的析取程序可以确定计算稳定模型的正常程序。因此，正常程序的稳定模型的实现可以用作实现析取程序的核心引擎。通过构造一个以该系统为核心的析取程序稳定模型计算系统，证明了该方法的可行性。最后将此系统的效能与目前最先进的析取程式专用系统dlv作比较。
英文摘要：
The paper studies an implementation methodology for partial and disjunctive stable models where partiality and disjunctions are unfolded from a logic program so that an implementation of stable models for normal (disjunction-free) programs can be used as the core inference engine. The unfolding is done in two separate steps. Firstly, it is shown that partial stable models can be captured by total stable models using a simple linear and modular program transformation. Hence, reasoning tasks concerning partial stable models can be solved using an implementation of total stable models. Disjunctive partial stable models have been lacking implementations which now become available as the translation handles also the disjunctive case. Secondly, it is shown how total stable models of disjunctive programs can be determined by computing stable models for normal programs. Hence, an implementation of stable models of normal programs can be used as a core engine for implementing disjunctive programs. The feasibility of the approach is demonstrated by constructing a system for computing stable models of disjunctive programs using the smodels system as the core engine. The performance of the resulting system is compared to that of dlv which is a state-of-the-art special purpose system for disjunctive programs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
