确定树MSO理论的一种压缩方法

A. Montanari, G. Puppis
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引用次数: 2

摘要

本文将最初由Elgot和Rabin提出,后来由Carton和Thomas推广的收缩方法,从标记线性排序推广到彩色确定性树。我们提出的方法建立在树自动机的树不可区分性的适当概念上,这使我们能够将树自动机的可接受性问题的许多实例减少到涉及规则树的可决定实例。我们证明了这种方法可以有效地处理大量的树,这些树在显著操作下是封闭的,并且包括通过展开和逆有限映射获得的所有caual层次的确定性树以及该层次之外的若干树。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Contraction Method to Decide MSO Theories of Deterministic Trees
In this paper we generalize the contraction method, originally proposed by Elgot and Rabin and later extended by Carton and Thomas, from labeled linear orderings to colored deterministic trees. The method we propose rests on a suitable notion of indistinguishability of trees with respect to tree automata that allows us to reduce a number of instances of the acceptance problem for tree automata to decidable instances involving regular trees. We prove that such a method works effectively for a large class of trees, which is closed under noticeable operations and includes all the deterministic trees of the Caucal hierarchy obtained via unfoldings and inverse finite mappings as well as several trees outside such a hierarchy.
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