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Tableau Calculi for Logic Programs under Answer Set Semantics

机译:答案集语义下的逻辑程序的Tableau计算

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We introduce formal proof systems based on tableau methods for analyzing computations in Answer Set Programming (ASP). Our approach furnishes fine-grained instruments for characterizing operations as well as strategies of ASP solvers. The granularity is detailed enough to capture a variety of propagation and choice methods of algorithms used for ASP solving, also incorporating SAT-based and conflict-driven learning approaches to some extent. This provides us with a uniform setting for identifying and comparing fundamental properties of ASP solving approaches. In particular, we investigate their proof complexities and show that the run-times of best-case computations can vary exponentially between different existing ASP solvers. Apart from providing a framework for comparing ASP solving approaches, our characterizations also contribute to their understanding by pinning down the constitutive atomic operations. Furthermore, our framework is flexible enough to integrate new inference patterns, and so to study their relation to existing ones. To this end, we generalize our approach and provide an extensible basis aiming at a modular incorporation of additional language constructs. This is exemplified by augmenting our basic tableau methods with cardinality constraints and disjunctions.
机译:我们介绍了基于表格方法的形式化证明系统,用于分析答案集编程(ASP)中的计算。我们的方法提供了用于描述操作以及ASP求解器策略的细粒度工具。粒度足够详细,可以捕获用于ASP解决的算法的各种传播和选择方法,并且在某种程度上还结合了基于SAT和冲突驱动的学习方法。这为我们提供了一个统一的设置,用于识别和比较ASP解决方法的基本属性。特别是,我们调查了它们的证明复杂性,并表明最佳情况下计算的运行时间在不同的现有ASP求解器之间可能呈指数变化。除了提供用于比较ASP解决方案的框架外,我们的特性还通过固定本构原子操作来帮助他们理解。此外,我们的框架足够灵活以集成新的推理模式,从而研究它们与现有推理模式的关系。为此,我们对方法进行了概括,并提供了可扩展的基础,旨在以模块化方式结合其他语言结构。这可以通过用基数约束和析取来扩充我们的基本表格方法来举例说明。

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