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Polynomial Identification of [Formula: see text]-Automata

We study identification in the limit using polynomial time and data for models of [Formula: see text]-automata. On the negative side we show that non-deterministic [Formula: see text]-automata (of types Büchi, coBüchi, Parity or Muller) can not be polynomially learned in the limit. On the positive s...

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Autores principales: Angluin, Dana, Fisman, Dana, Shoval, Yaara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480709/
http://dx.doi.org/10.1007/978-3-030-45237-7_20
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author Angluin, Dana
Fisman, Dana
Shoval, Yaara
author_facet Angluin, Dana
Fisman, Dana
Shoval, Yaara
author_sort Angluin, Dana
collection PubMed
description We study identification in the limit using polynomial time and data for models of [Formula: see text]-automata. On the negative side we show that non-deterministic [Formula: see text]-automata (of types Büchi, coBüchi, Parity or Muller) can not be polynomially learned in the limit. On the positive side we show that the [Formula: see text]-language classes [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] that are defined by deterministic Büchi, coBüchi, parity, and Muller acceptors that are isomorphic to their right-congruence automata (that is, the right congruences of languages in these classes are fully informative) are identifiable in the limit using polynomial time and data. We further show that for these classes a characteristic sample can be constructed in polynomial time.
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spelling pubmed-74807092020-09-10 Polynomial Identification of [Formula: see text]-Automata Angluin, Dana Fisman, Dana Shoval, Yaara Tools and Algorithms for the Construction and Analysis of Systems Article We study identification in the limit using polynomial time and data for models of [Formula: see text]-automata. On the negative side we show that non-deterministic [Formula: see text]-automata (of types Büchi, coBüchi, Parity or Muller) can not be polynomially learned in the limit. On the positive side we show that the [Formula: see text]-language classes [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] that are defined by deterministic Büchi, coBüchi, parity, and Muller acceptors that are isomorphic to their right-congruence automata (that is, the right congruences of languages in these classes are fully informative) are identifiable in the limit using polynomial time and data. We further show that for these classes a characteristic sample can be constructed in polynomial time. 2020-03-13 /pmc/articles/PMC7480709/ http://dx.doi.org/10.1007/978-3-030-45237-7_20 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
Angluin, Dana
Fisman, Dana
Shoval, Yaara
Polynomial Identification of [Formula: see text]-Automata
title Polynomial Identification of [Formula: see text]-Automata
title_full Polynomial Identification of [Formula: see text]-Automata
title_fullStr Polynomial Identification of [Formula: see text]-Automata
title_full_unstemmed Polynomial Identification of [Formula: see text]-Automata
title_short Polynomial Identification of [Formula: see text]-Automata
title_sort polynomial identification of [formula: see text]-automata
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480709/
http://dx.doi.org/10.1007/978-3-030-45237-7_20
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