摘要翻译：
给出了一个论证框架AF，引入映射函数构造了一个析取逻辑程序P，使AF的首选扩展对应于P的稳定模型，然后将每个稳定模型与相关原子相交。给出的映射函数是多项式大小的W.R.T。特别地，我们通过对失败论据的表示，发现命题公式的最小模型与论证框架的首选扩展之间存在直接关系。然后，我们展示了如何利用非SAT算法和析取稳定模型求解器来推断一个论证框架的首选扩展。这一结果的相关性在于，我们定义了一种最令人满意的论证语义与一种最成功的非单调推理方法，即具有稳定模型语义的逻辑程序设计之间的直接关系。
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英文标题：
《Preferred extensions as stable models》
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作者：
Juan Carlos Nieves, Mauricio Osorio, Ulises Cort\'es
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Computer Science        计算机科学
二级分类：Symbolic Computation        符号计算
分类描述：Roughly includes material in ACM Subject Class I.1.
大致包括ACM学科第一类1的材料。
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英文摘要：
  Given an argumentation framework AF, we introduce a mapping function that constructs a disjunctive logic program P, such that the preferred extensions of AF correspond to the stable models of P, after intersecting each stable model with the relevant atoms. The given mapping function is of polynomial size w.r.t. AF. In particular, we identify that there is a direct relationship between the minimal models of a propositional formula and the preferred extensions of an argumentation framework by working on representing the defeated arguments. Then we show how to infer the preferred extensions of an argumentation framework by using UNSAT algorithms and disjunctive stable model solvers. The relevance of this result is that we define a direct relationship between one of the most satisfactory argumentation semantics and one of the most successful approach of non-monotonic reasoning i.e., logic programming with the stable model semantics.
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PDF链接：
https://arxiv.org/pdf/0803.3812