摘要翻译：
逻辑程序设计已经发展成为一个丰富的领域，建立在一个逻辑基础之上，其主要组成部分是非经典形式的否定，有时与经典否定共存。该领域已经出现了许多替代语义学，其中Kripke-Kleene语义学、有根据语义学、稳定模型语义学和答案集语义学是最成功的语义学。我们表明，在一个框架中，所有上述语义学都是泛型语义学的特例，在这个框架中，古典否定是否定的独特形式，在这个框架中，规则正文中的字面可以被标记，以表明它们可以成为假设的目标。一个特定的语义就等于选择一个特定的标记方案和一组特定的假设。当一个字面属于所选择的假说集合时，假定该字面在规则正文中的所有标记的出现都是真的，而该字面在规则正文中没有标记的出现是为了促进规则的触发而推导出来的。因此，在这个框架中提出的假设推理的概念不是基于做出全局假设，而是更微妙地基于做出局部的、上下文的假设，在所选择的假设集合的基础上，按照所选择的标记方案所指示的那样生效。我们的方法对逻辑程序设计中提出的各种语义提供了一个统一的观点，经典的是只使用经典的否定，并将逻辑程序的语义与赋予基于规则的系统利用假设推理的能力的机制联系起来。
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英文标题：
《Contextual hypotheses and semantics of logic programs》
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作者：
\'Eric A. Martin
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Logic in Computer Science        计算机科学中的逻辑
分类描述：Covers all aspects of logic in computer science, including finite model theory, logics of programs, modal logic, and program verification. Programming language semantics should have Programming Languages as the primary subject area. Roughly includes material in ACM Subject Classes D.2.4, F.3.1, F.4.0, F.4.1, and F.4.2; some material in F.4.3 (formal languages) may also be appropriate here, although Computational Complexity is typically the more appropriate subject area.
涵盖计算机科学中逻辑的所有方面，包括有限模型理论，程序逻辑，模态逻辑和程序验证。程序设计语言语义学应该把程序设计语言作为主要的学科领域。大致包括ACM学科类D.2.4、F.3.1、F.4.0、F.4.1和F.4.2中的材料；F.4.3（形式语言）中的一些材料在这里也可能是合适的，尽管计算复杂性通常是更合适的主题领域。
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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：
  Logic programming has developed as a rich field, built over a logical substratum whose main constituent is a nonclassical form of negation, sometimes coexisting with classical negation. The field has seen the advent of a number of alternative semantics, with Kripke-Kleene semantics, the well-founded semantics, the stable model semantics, and the answer-set semantics standing out as the most successful. We show that all aforementioned semantics are particular cases of a generic semantics, in a framework where classical negation is the unique form of negation and where the literals in the bodies of the rules can be `marked' to indicate that they can be the targets of hypotheses. A particular semantics then amounts to choosing a particular marking scheme and choosing a particular set of hypotheses. When a literal belongs to the chosen set of hypotheses, all marked occurrences of that literal in the body of a rule are assumed to be true, whereas the occurrences of that literal that have not been marked in the body of the rule are to be derived in order to contribute to the firing of the rule. Hence the notion of hypothetical reasoning that is presented in this framework is not based on making global assumptions, but more subtly on making local, contextual assumptions, taking effect as indicated by the chosen marking scheme on the basis of the chosen set of hypotheses. Our approach offers a unified view on the various semantics proposed in logic programming, classical in that only classical negation is used, and links the semantics of logic programs to mechanisms that endow rule-based systems with the power to harness hypothetical reasoning.
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PDF链接：
https://arxiv.org/pdf/0901.0733