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Possibilistic Inferences in Answer Set Programming

机译:答案集编程中的可能性推论

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Answer set programming (ASP) has been extended to possibilistic ASP (PASP), in which the notion of possibilistic stable models is defined for possibilistic logic programs. However, possibilistic inferences that correspond to the three inferences in ordinary possibilistic logic have not been explored in PASP yet. In this paper, based on the skeptical reasoning determined by possibilistic stable models, we define three inference relations for PASP, provide their equivalent characterisations in terms of possibility distribution, and develop algorithms for these possibilistic inferences. Our algorithms are achieved by generalising some important concepts (Clarke's completion, loop formulas, and guarded resolution) and properties in ASP to PASP. Besides their theoretical importance, these results can be used to develop efficient implementations for possibilistic reasoning in ASP.
机译:回答设置编程(ASP)已扩展到可能的ASP(PASP),其中对于可能性逻辑程序定义了可能的稳定模型的概念。然而,对应于普通可能主义逻辑的三次推论的可能性推论尚未申请。在本文中,基于由可能的稳定模型确定的持怀疑态度,我们定义了三个PASP的推理关系,提供了它们在可能性分布方面的等效特征,以及为这些可能性推论的开发算法。我们的算法是通过推广一些重要的概念(Clarke的完成,循环公式和保护分辨率)和ASP的属性来实现的。除了他们的理论重要性,这些结果可用于开发ASP中可能性原理的有效实现。

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