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Identification of Function Distinguishable Languages

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Algorithmic Learning Theory (ALT 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1968))

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Abstract

We show how appropriately chosen functions which we call distinguishing can be used to make deterministic finite automata backward deterministic. These ideas can be exploited to design regular language classes identifiable in the limit from positive samples. Special cases of this approach are the k-reversible and terminal distinguishable languages as discussed in [1],[8],[10],[17],[18].

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Author information

Authors and Affiliations

  1. Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Sand 13, D-72076, Tübingen, Germany

    Henning Fernau

Authors
  1. Henning Fernau
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Editor information

Editors and Affiliations

  1. Department of Informatics, Kyushu University, Hakozaki 6-10-1, 812-8581, Fukuoka, Japan

    Hiroki Arimura

  2. School of Computing, National University of Singapore, 3 Science Drive 2, 117543, Singapore, Singapore

    Sanjay Jain

  3. School of Computer Science and Engineering, The University of New South Wales, 2052, Sydney, Australia

    Arun Sharma

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© 2000 Springer-Verlag Berlin Heidelberg

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Fernau, H. (2000). Identification of Function Distinguishable Languages. In: Arimura, H., Jain, S., Sharma, A. (eds) Algorithmic Learning Theory. ALT 2000. Lecture Notes in Computer Science(), vol 1968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40992-0_9

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  • DOI: https://doi.org/10.1007/3-540-40992-0_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41237-3

  • Online ISBN: 978-3-540-40992-2

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