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Using domain information during the learning of a subsequential transducer

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Grammatical Interference: Learning Syntax from Sentences (ICGI 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1147))

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Abstract

The recently proposed OSTI algorithm allows for the identification of subsequential functions from input-output pairs. However, if the target is a partial function the convergence is not guaranteed. In this work, we extend the algorithm in order to allow for the identification of any partial subsequential function provided that either a negative sample or a description of the domain by means of a deterministic finite automaton is available.

This work has been partially supported by the Spanish CICYT under contract TIC93-0633-C02 & TIC95-0984-C02-01

Miguel A. Varó is supported by a postgraduate grant from the Generalitat Valenciana (local government)

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Authors and Affiliations

  1. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, E-03071, Alicante, Spain

    Jose Oncina & Miguel Angel Varó

Authors
  1. Jose Oncina
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  2. Miguel Angel Varó
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Laurent Miclet Colin de la Higuera

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© 1996 Springer-Verlag Berlin Heidelberg

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Oncina, J., Varó, M.A. (1996). Using domain information during the learning of a subsequential transducer. In: Miclet, L., de la Higuera, C. (eds) Grammatical Interference: Learning Syntax from Sentences. ICGI 1996. Lecture Notes in Computer Science, vol 1147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033364

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  • DOI: https://doi.org/10.1007/BFb0033364

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61778-5

  • Online ISBN: 978-3-540-70678-6

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