Introducing Quantification into a Hierarchical Graph Rewriting Language

Haruto Mishina, Kazunori Ueda
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Abstract

LMNtal is a programming and modeling language based on hierarchical graph rewriting that uses logical variables to represent connectivity and membranes to represent hierarchy. On the theoretical side, it allows logical interpretation based on intuitionistic linear logic; on the practical side, its full-fledged implementation supports a graph-based parallel model checker and has been used to model diverse applications including various computational models. This paper discuss how we extend LMNtal to QLMNtal (LMNtal with Quantification) to further enhance the usefulness of hierarchical graph rewriting for high-level modeling by introducing quantifiers into rewriting as well as matching. Those quantifiers allows us to express universal quantification, cardinality and non-existence in an integrated manner. Unlike other attempts to introduce quantifiers into graph rewriting, QLMNtal has term-based syntax, whose semantics is smoothly integrated into the small-step semantics of the base language LMNtal. The proposed constructs allow combined and nested use of quantifiers within individual rewrite rules.
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将量化引入层次图重写语言
LMNtal 是一种基于分层图重写的编程和建模语言,它使用逻辑变量来表示连接性,使用膜来表示层次结构。在理论方面,它允许基于直觉线性逻辑的逻辑解释;在实践方面,它的完整实现支持基于图的并行模型检查器,并已被用于包括各种计算模型在内的多种应用建模。本文讨论了我们如何将 LMNtal 扩展为 QLMNtal(带量词的 LMNtal),通过在重写和匹配中引入量词,进一步增强分层图重写在高层建模中的实用性。这些量词使我们能够以一种综合的方式表达通用量词、卡片性和不存在性。与其他在图重写中引入量词的尝试不同,QLMNtal 具有基于term的语法,其语义可以平滑地集成到基础语言 LMNtal 的小步语义中。所提出的构造允许在单个重写规则中组合和嵌套使用量词。
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