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A Proposal for Contextual Grammatical Inference

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Advances in Computational Intelligence (IWANN 2015)

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Abstract

Grammatical Inference deals with the learning of formal languages from data. Research in this field has mainly reduced the problem of language learning to syntax learning. Taking into account that the theoretical results obtained in Grammatical Inference show that learning formal languages only from syntax is generally hard, in this paper we propose to also take into account contextual information during the language learning process. First, we review works in the area of Artificial Intelligence that use the concept of context, and then, we present the theoretical, algorithmic and practical aspects of our proposal.

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Author information

Authors and Affiliations

  1. Laboratoire Hubert Curien, Jean Monnet University, 18 rue Benoit Lauras, 42000, Saint-Etienne, France

    Leonor Becerra-Bonache, María Galván & François Jacquenet

Authors
  1. Leonor Becerra-Bonache
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  2. María Galván
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  3. François Jacquenet
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Corresponding author

Correspondence to Leonor Becerra-Bonache .

Editor information

Editors and Affiliations

  1. University of Granada, Granada, Spain

    Ignacio Rojas

  2. University of Malaga, Malaga, Spain

    Gonzalo Joya

  3. Polytechnic University of Catalonia, Vilanova i la Geltrú, Spain

    Andreu Catala

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Becerra-Bonache, L., Galván, M., Jacquenet, F. (2015). A Proposal for Contextual Grammatical Inference. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2015. Lecture Notes in Computer Science(), vol 9094. Springer, Cham. https://doi.org/10.1007/978-3-319-19258-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-19258-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19257-4

  • Online ISBN: 978-3-319-19258-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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