Learning regular omega languages

@article{Angluin2016LearningRO,
  title={Learning regular omega languages},
  author={Dana Angluin and Dana Fisman},
  journal={Theor. Comput. Sci.},
  year={2016},
  volume={650},
  pages={57-72}
}
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 omega regular languages, using the notion of families of dfas. One is of size similar to L$, a dfa representation recently learned using L ∗ [7]. The second is based on the syntactic forc, introduced in [14]. The third is introduced herein. We show that the second can be exponentially smaller… CONTINUE READING

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