lntroducing generalized specificity in logic programming
lntroducing generalized specificity in logic programming
复制标题
在逻辑编程中引入广义特异性
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
Guillermo R. Simari
中科院分区：
文献类型：
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作者：
Frieder Stolzenburg;A. García;C. Chesñevar;Guillermo R. Simari
大多数用于表示常识知识的形式主义允许不完整和潜在不一致的信息。当也允许强烈否定时，可能会出现相互矛盾的结论。因此，需要一个标准来决定它们之间的关系。逻辑编程的几个扩展考虑程序（默认）规则的优先级。然而，这些优先级必须由程序员以或多或少的任意方式提供，明确地建立规则之间的关系。本文的目的是超越规则之间的显式比较，寻找一个内在的和自主的比较标准，基于[22，25]中定义的特异性。与其他方法相比，我们认为不仅可废止，而且严格的知识。我们比较论点的标准，即具体性，是上下文敏感的。这意味着在辩证分析过程中，可废止规则的偏好是动态确定的。我们展示了如何这样的特异性标准可以定义在两种不同的方法：激活集和派生树。这使我们能够得到一个更语法的标准，可以在计算上有吸引力的方式实现。由此产生的定义可以应用在一个通用的基于规则的形式主义。我们提出了一个定理，这两个特征，显示它们的等价性。最后，我们讨论了其他框架的可废止推理，其中偏好处理被认为是明确的，对比他们与我们的方法。
Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory conclusions can arise. Therefore, a criterion for deciding between them is needed. Several extensions of logic programming consider priorities over program (default) rules. However, these priorities must be supplied by the programmer in a more or less arbitrary manner, establishing explicitly relations between rules. The aim of this paper is to investigate beyond explicit comparison between rules, looking for an inherent and autonomous comparison criterion, based on specificity as defined in [22, 25]. In contrast to other approaches, we consider not only defeasible, but also strict knowledge. Our criterion for comparing arguments, namely specificity, is context-sensitive. This means that preference among defeasible rules is determined dynamically during the dialectical analysis. We show how such a specificity criterion can be defined in terms of two different approaches: activation sets and derivation trees. This allows us to get a more syntactic criterion that can be implemented in a computationally attractive way. The resulting definitions may be applied in a generic rule-based formalism. We present a theorem which links both characterizations, showing their equivalence. Finally we discuss other frameworks for defeasible reasoning in which preference handling is considered explicitly, contrasting them with our approach.