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Inferring Deterministic Linear Languages

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Computational Learning Theory (COLT 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2375))

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Abstract

Linearity and determinism seem to be two essential conditions for polynomial language learning to be possible. We compare several definitions of deterministic linear grammars, and for a reasonable definition prove the existence of a canonical normal form. This enables us to obtain positive learning results in case of polynomial learning from a given set of both positive and negative examples. The resulting class is the largest one for which this type of results has been obtained so far.

This work was done when the first author visited the Departamento de Lenguajes y Sistemas Informáticos of the University of Alicante, Spain. The visit was sponsored by the Spanish Ministry of Education.

The second author thanks the Spanish CICyT for partial support of this work through project TIC2000-1703-C03-02.

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Author information

Authors and Affiliations

  1. EURISE, Université de Saint-Etienne, 23 rue du Docteur Paul Michelon, 42023, Saint-Etienne, France

    Colin de la Higuera

  2. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Ap.99, E-03080, Alicante, Spain

    Jose Oncina

Authors
  1. Colin de la Higuera
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  2. Jose Oncina
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Editors and Affiliations

  1. Research School of Information Sciences and Engineering, Australian National University, Canberra, ACT, 0200, Australia

    Jyrki Kivinen

  2. Computer Science Department, University of Illinois at Chicago, 851 S. Morgan St., Chicago, IL, 60607, USA

    Robert H. Sloan

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© 2002 Springer-Verlag Berlin Heidelberg

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de la Higuera, C., Oncina, J. (2002). Inferring Deterministic Linear Languages. In: Kivinen, J., Sloan, R.H. (eds) Computational Learning Theory. COLT 2002. Lecture Notes in Computer Science(), vol 2375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45435-7_13

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  • DOI: https://doi.org/10.1007/3-540-45435-7_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43836-6

  • Online ISBN: 978-3-540-45435-9

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