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International Colloquium on Grammatical Inference

ICGI 2002: Grammatical Inference: Algorithms and Applications pp 225–236Cite as

Learning Locally Testable Even Linear Languages from Positive Data

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2484))

Abstract

Learning from positive data is a center goal in grammatical inference. Some language classes have been characterized in order to allow its learning from text. There are two different approaches to this topic: (i) reducing the new classes to well known ones, and (ii) designing new learning algorithms for the new classes. In this work we will use reduction techniques to define new classes of even linear languages which can be inferred from positive data only. We will center our attention to inferable classes based on local testability features. So, the learning processes for such classes of even linear languages can be performed by using algorithms for locally testable regular languages.

Work supported by the Spanish CICYT under contract TIC2000-1153.

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Author information

Authors and Affiliations

  1. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Valencia, Spain

    José M. Sempere & Pedro García

Authors
  1. José M. Sempere
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  2. Pedro García
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Editor information

Editors and Affiliations

  1. Perot Systems Nederland B.V., Hoefseweg 1, 3821 AE, Amersfoort, The Netherlands

    Pieter Adriaans (Senior Research Advisor, Professor of Learning and Adaptive Systems) (Senior Research Advisor, Professor of Learning and Adaptive Systems)

  2. ILLC/Computation and Complexity Theory, Universiteit van Amsterdam, Plantage Muidergracht 24, 1018 TV, Amsterdam, The Netherlands

    Pieter Adriaans (Senior Research Advisor, Professor of Learning and Adaptive Systems) (Senior Research Advisor, Professor of Learning and Adaptive Systems)

  3. School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia

    Henning Fernau

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

    Henning Fernau

  5. FNWI/ILLC, Cognitive Systems and Information Processing Group, Universiteit van Amsterdam, Room B-5.39, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands

    Menno van Zaanen

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© 2002 Springer-Verlag Berlin Heidelberg

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Sempere, J.M., García, P. (2002). Learning Locally Testable Even Linear Languages from Positive Data. In: Adriaans, P., Fernau, H., van Zaanen, M. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2002. Lecture Notes in Computer Science(), vol 2484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45790-9_18

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  • DOI: https://doi.org/10.1007/3-540-45790-9_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44239-4

  • Online ISBN: 978-3-540-45790-9

  • eBook Packages: Springer Book Archive

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