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Polynomial-Time Identification of Multiple Context-Free Languages from Positive Data and Membership Queries

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Grammatical Inference: Theoretical Results and Applications (ICGI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6339))

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Abstract

This paper presents an efficient algorithm that identifies a rich subclass of multiple context-free languages in the limit from positive data and membership queries by observing where each tuple of strings may occur in sentences of the language of the learning target. Our technique is based on Clark et al.’s work (ICGI 2008) on learning of a subclass of context-free languages. Our algorithm learns those context-free languages as well as many non-context-free languages.

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Author information

Authors and Affiliations

  1. Minato Discrete Structure Manipulation System Project, Japan Science and Technology Agency, Erato

    Ryo Yoshinaka

Authors
  1. Ryo Yoshinaka
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Editor information

Editors and Affiliations

  1. Departamento de Sistemas Informáticos y Computatión, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

    José M. Sempere  & Pedro García  & 

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Yoshinaka, R. (2010). Polynomial-Time Identification of Multiple Context-Free Languages from Positive Data and Membership Queries. In: Sempere, J.M., García, P. (eds) Grammatical Inference: Theoretical Results and Applications. ICGI 2010. Lecture Notes in Computer Science(), vol 6339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15488-1_19

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  • DOI: https://doi.org/10.1007/978-3-642-15488-1_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15487-4

  • Online ISBN: 978-3-642-15488-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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