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Deciding Context Unification (with Regular Constraints)

机译:确定上下文统一(带有常规约束)

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Given a ranked alphabet, context are terms with a single occurrence of a special symbol • (outside of the alphabet), which represents a missing subterm. One can naturally build equations over contexts: the context variables are treated as symbols of arity one and a substitution S assigns to each such a variable a context S(X). A substitution S is extended to terms with context variables in a natural way: S(X(t)) is a context S(X) in which the unique occurrence of • is replaced with S(t). For historical reasons, the satisfiability of context equations is usually referred to as context unification. Context unification generalizes word equations and first-order term unification (which are decidable) and is subsumed by second order unification (which is undecidable) and its decidability status remained open for almost two decades. In this paper I will sketch a PSPACE algorithm for this problem. The idea is to apply simple compression rules (replacing pairs of neighbouring function symbols) to the solution of the context equation; to this end we appropriately modify the equation (without the knowledge of the actual solution) so that compressing the solution can be simulated by compressing parts of the equation. When the compression operations are appropriately chosen, then the size of the instance is polynomial during the whole algorithm, thus giving a PSPACE-upper bound. The best known lower bounds are as for word equations, i.e. NP. The method can be extended to the scenario in which tree-regular constraints for the variables are present, in which case the problem is EXPTIME-complete.
机译:在给定排名的字母的情况下,上下文是指一次出现特殊符号•(在字母外部)的术语,表示缺少的子术语。可以自然地根据上下文建立方程式:将上下文变量视为符号1,并且替换S为每个此类变量分配上下文S(X)。替换S以自然的方式扩展到带有上下文变量的项:S(X(t))是上下文S(X),其中唯一的•替换为S(t)。由于历史原因,上下文方程式的可满足性通常称为上下文统一。上下文统一概括了单词方程式和一阶项统一(可确定),并归入二阶统一(不可确定),其可确定性状态开放了将近二十年。在本文中,我将为这个问题画一个PSPACE算法。想法是将简单的压缩规则(替换成对的相邻函数符号)应用于上下文方程的解;为此,我们在不了解实际解的情况下适当地修改了方程,以便可以通过压缩方程的一部分来模拟压缩解。当压缩操作被适当地选择,则该实例的大小在整个算法中是多项式,从而得到PSPACE-上限。最著名的下限与单词方程(即NP)相同。该方法可以扩展到存在变量的树规则约束的情况,在这种情况下,问题是EXPTIME完全的。

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