摘要翻译：
通过将因果关系理论与违约理论相结合，弥补了Halpern-Pearl(HP)因果关系定义的一个严重缺陷。此外，它表明（尽管有相反的主张）根据HP条件的原因不一定是单一的联合。由赖特的NESS检验所激发的因果关系的定义被证明总是对一个单一的联合成立。此外，对于HP所考虑的所有例子都给出了成立的条件，这些条件保证了根据（这个版本）NESS检验的因果关系与HP定义是等价的。
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英文标题：
《Defaults and Normality in Causal Structures》
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作者：
Joseph Y. Halpern
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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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英文摘要：
  A serious defect with the Halpern-Pearl (HP) definition of causality is repaired by combining a theory of causality with a theory of defaults. In addition, it is shown that (despite a claim to the contrary) a cause according to the HP condition need not be a single conjunct. A definition of causality motivated by Wright's NESS test is shown to always hold for a single conjunct. Moreover, conditions that hold for all the examples considered by HP are given that guarantee that causality according to (this version) of the NESS test is equivalent to the HP definition.
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PDF链接：
https://arxiv.org/pdf/0806.2140