摘要翻译：
易失性论证框架已经发展成为一种健全的环境，可以形式化常识，从不完整和潜在不一致的知识中进行定性推理。可拆卸逻辑程序设计(DeLP)是基于逻辑程序设计的一种可拆卸论证形式。尽管DeLP已经成功地集成在许多不同的实际应用中，但是DeLP不能处理显式的不确定性，也不能处理模糊的知识，因为失败性是直接用对象语言编码的。本文介绍了一种新的逻辑程序设计语言P-DeLP，它扩展了原有DeLP的定性推理能力，结合了对可能性不确定性和模糊知识的处理。这些特征将在基于哥德尔模糊逻辑的可能性逻辑PGL的基础上形式化。
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英文标题：
《A Logic Programming Framework for Possibilistic Argumentation with Vague
  Knowledge》
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作者：
Carlos Chesnevar, Guillermo Simari, Teresa Alsinet, Lluis Godo
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最新提交年份：
2012
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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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英文摘要：
  Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible argumentation formalism based on an extension of logic programming. Although DeLP has been successfully integrated in a number of different real-world applications, DeLP cannot deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper introduces P-DeLP, a new logic programming language that extends original DeLP capabilities for qualitative reasoning by incorporating the treatment of possibilistic uncertainty and fuzzy knowledge. Such features will be formalized on the basis of PGL, a possibilistic logic based on Godel fuzzy logic.
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PDF链接：
https://arxiv.org/pdf/1207.4123