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A model theory for nonmonotonic multiple value and code inheritance in object-oriented knowledge bases.

机译:面向对象知识库中非单调多值和代码继承的模型理论。

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摘要

We have developed a comprehensive model theory for nonmonotonic multiple value and code inheritance in object-oriented knowledge bases. Our new inheritance semantics, called optimistic object model semantics, supports implicit inference by inheritance as well as explicit deductive inference via rules. Inference by inheritance supports a multitude of features, such as overriding, nonmonotonic multiple value and code inheritance, meta programming, and dynamic class hierarchies—the important features that are fundamental to advanced object-oriented knowledge management.; In the setting of three-valued models, we formally define the inheritance postulates that capture the common intuition behind overriding and conflict resolution in nonmonotonic multiple value and code inheritance. These postulates specify the minimum requirements for object models.; We specify an extended alternating fixpoint procedure for computing object models. We define a unique object model, called optimistic object model, for any given program that is written in our rule-based query language. We prove three different characterizations of the optimistic object model semantics: an optimistic object model is the least fixpoint of the extended alternating fixpoint computation, is the least stable object model with respect to information ordering, and is a minimal object model with respect to truth ordering.; Our new inheritance semantics yields intuitively satisfactory results in all known benchmark cases, does not impose syntactic restrictions on programs, and has been implemented in the Flora-2 system. To the best of our knowledge, the optimistic object model semantics is currently the only model-theoretic semantics for nonmonotonic multiple value and code inheritance that applies to general, unrestricted object-oriented knowledge bases.
机译:我们已经为面向对象的知识库中的非单调多重值和代码继承开发了一种全面的模型理论。我们的新继承语义称为乐观对象模型语义,它支持通过继承进行隐式推理以及通过规则进行显式演绎推理。继承推断支持多种功能,例如覆盖,非单调多值和代码继承,元编程和动态类层次结构,这些是高级面向对象知识管理的基础。在三值模型的设置中,我们正式定义了继承假设,这些继承假设捕获了非单调多值和代码继承中的覆盖和冲突解决背后的常见直觉。这些假设规定了对象模型的最低要求。我们指定了用于计算对象模型的扩展交替定点过程。我们为使用基于规则的查询语言编写的任何给定程序定义一个唯一的对象模型,称为乐观对象模型。我们证明了乐观对象模型语义的三种不同特征:乐观对象模型是扩展交替定点计算的最小定点,相对于信息排序是最不稳定的对象模型,相对于真值排序是最小的对象模型。;我们的新继承语义在所有已知基准情况下都能产生直观令人满意的结果,不对程序施加语法限制,并且已在Flora-2系统中实现。就我们所知,乐观对象模型语义是当前唯一适用于一般的,不受限制的面向对象知识库的非单调多值和代码继承的模型理论语义。

著录项

  • 作者

    Yang, Guizhen.;

  • 作者单位

    State University of New York at Stony Brook.;

  • 授予单位 State University of New York at Stony Brook.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2002
  • 页码 101 p.
  • 总页数 101
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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