@inproceedings{4b5d93c9b3dd4df1802c30afdf5d948c,
title = "Learning regular omega languages",
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.",
author = "Dana Angluin and Dana Fisman",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 25th International Conference on Algorithmic Learning Theory, ALT 2014 ; Conference date: 08-10-2014 Through 10-10-2014",
year = "2014",
month = jan,
day = "1",
doi = "https://doi.org/10.1007/978-3-319-11662-4_10",
language = "American English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "125--139",
editor = "Peter Auer and Alexander Clark and Thomas Zeugmann and Sandra Zilles",
booktitle = "Algorithmic Learning Theory - 25th International Conference, ALT 2014, Proceedings",
address = "Germany",
}