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Minimizing Generalized Buechi Automata

机译:最小化广义Buechi自动机

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摘要

We consider the problem of minimization of generalized Buechi automata. We extend fair-simulation minimization and delayed-simulation minimization to the case where the Buechi automaton has multiple acceptance conditions. For fair simulation, we show how to efficiently compute the fair-simulation relation while maintaining the structure of the automaton. We then use the fair-simulation relation to merge states and remove transitions. Our fair-simulation algorithm works in time O(mn~3k~2) where m is the number of transitions, n is the number of states, and k is the number of acceptance sets. For delayed simulation, we extend the existing definition to the case of multiple acceptance conditions. We show that our definition can indeed be used for minimization and give an algorithm that computes the delayed-simulation relation. Our delayed-simulation algorithm works in time O(mn~3k). We implemented the two algorithms and report on experimental results.
机译:我们考虑了广义Buechi自动机最小化的问题。我们将公平仿真最小化和延迟仿真最小化扩展到Buechi自动机具有多个接受条件的情况。对于公平仿真,我们展示了如何在保持自动机结构的同时有效地计算公平仿真关系。然后,我们使用公平仿真关系合并状态并删除过渡。我们的公平仿真算法在时间O(mn〜3k〜2)内起作用,其中m是转移数,n是状态数,k是接受集数。对于延迟仿真,我们将现有定义扩展到多个接受条件的情况。我们证明了我们的定义确实可以用于最小化,并给出了一种计算延迟仿真关系的算法。我们的延迟仿真算法的工作时间为O(mn〜3k)。我们实现了这两种算法并报告了实验结果。

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