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Learning Regular Omega Languages

  • Dana Angluin
  • Dana Fisman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8776)

Abstract

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 than the first, and the third is at most as large as the first two, with up to a quadratic saving with respect to the second.

Keywords

Regular Language Canonical Representation Acceptance Condition Membership Query Equivalence Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Dana Angluin
    • 1
  • Dana Fisman
    • 2
  1. 1.Yale UniversityNew HavenUSA
  2. 2.University of PennsylvaniaPhiladelphiaUSA

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