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arXiv 2104.14175cs.LO
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Initial Limit Datalog:一类新的可扩展可判定约束Horn子句

Initial Limit Datalog: a New Extensible Class of Decidable Constrained Horn Clauses

Toby Cathcart Burn, Luke Ong, Steven Ramsay, Dominik Wagner

摘要:

我们提出了初始极限数据库,一个新的可扩展类的约束霍恩条款的可满足性问题是可判定的。这个类可以被看作是一阶语言极限数据集$_Z$(数据集模线性整数运算的一个片段)的高阶逻辑(对类型有简单的限制)的推广,但是可以用任何合适的背景理论来实例化。例如,片段是可判定的任何可数良好的准序与可判定的一阶理论,如自然数向量下的分量线性算术,和有界的,上下文无关的语言的字排序的子字关系。在背景理论的某些假设下,初始极限公式的可满足性可以通过一种新的项模型来证明,我们称之为集合结构。虽然所有模型的集合通常是不可数的,但所有可枚举结构的集合是递归可枚举的,并且模型检验是可判定的。

英文摘要:

We present initial limit Datalog, a new extensible class of constrained Horn clauses for which the satisfiability problem is decidable. The class may be viewed as a generalisation to higher-order logic (with a simple restriction on types) of the first-order language limit Datalog$_Z$ (a fragment of Datalog modulo linear integer arithmetic), but can be instantiated with any suitable background theory. For example, the fragment is decidable over any countable well-quasi-order with a decidable first-order theory, such as natural number vectors under componentwise linear arithmetic, and words of a bounded, context-free language ordered by the subword relation. Formulas of initial limit Datalog have the property that, under some assumptions on the background theory, their satisfiability can be witnessed by a new kind of term model which we call entwined structures. Whilst the set of all models is typically uncountable, the set of all entwined structures is recursively enumerable, and model checking is decidable.

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