Fixpoint guided abstraction refinement for alternating automata

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Abstract

In this paper, we develop and evaluate two new algorithms for checking emptiness of alternating automata. These algorithms build on previous works. First, they rely on antichains to efficiently manipulate the state-spaces underlying the analysis of alternating automata. Second, they are abstract algorithms with built-in refinement operators based on techniques that exploit information computed by abstract fixed points (and not counter-examples as it is usually the case). The efficiency of our new algorithms is illustrated by experimental results. © 2009 Springer Berlin Heidelberg.

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Ganty, P., Maquet, N., & Raskin, J. F. (2009). Fixpoint guided abstraction refinement for alternating automata. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5642 LNCS, pp. 155–164). https://doi.org/10.1007/978-3-642-02979-0_19

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