Learning regular omega languages
摘要：
We provide an algorithm for learning an unknown regular set of infinite words using membership and equivalence queries. Three variations of the algorithm learn three different canonical representations of regular omega languages using the notion of families ofdfas. One is of size similar toL$, adfarepresentation recently learned usingLby Farzan et al. The second is based on the syntacticforc, introduced by Maler and Staiger. The third is introduced herein. We show that the second and third can be exponentially smaller than the first, and the third is at most as large as the second, with up to a quadratic saving with respect to the second.
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关键词：
Active learning Language inference Infinitary languages Membership queries Equivalence queries L⁎ Büchi automata
DOI：
10.1016/j.tcs.2016.07.031
被引量：
年份：
2016
Elsevier
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Semantic Scholar
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cs.bgu.ac.il
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seas.upenn.edu
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学术范
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