将稳定模型语义拓展到模糊命题公式，支持可配置的非单调推理。
Fuzzy Propositional Formulas under the Stable Model Semantics
- 基于模糊命题逻辑语法，定义新的稳定模型语义
- 继承布尔稳定模型多项性质，适用于多值真度场景
- 适合动态领域中带程度真值的非单调推理研究
我们为模糊命题公式定义了稳定模型语义，该语义同时推广了模糊命题逻辑和经典命题公式的稳定模型语义。语言语法与模糊命题逻辑相同，但语义上区分稳定模型与非稳定模型。该语言的通用性使得在涉及梯度真值度的动态领域中可实现高度可配置的非单调推理。我们证明了布尔稳定模型的若干性质可自然延拓至多值情形，并讨论了其与其他模糊逻辑与稳定模型语义结合方法的关系。
原文摘要 · Abstract (English)
We define a stable model semantics for fuzzy propositional formulas, which generalizes both fuzzy propositional logic and the stable model semantics of classical propositional formulas. The syntax of the language is the same as the syntax of fuzzy propositional logic, but its semantics distinguishes stable models from non-stable models. The generality of the language allows for highly configurable nonmonotonic reasoning for dynamic domains involving graded truth degrees. We show that several properties of Boolean stable models are naturally extended to this many-valued setting, and discuss how it is related to other approaches to combining fuzzy logic and the stable model semantics.
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