Revistes Publicacions URV: Triangle - llenguatge, literatura, computació> 2012

Learning SECp Languages from Only Positive Data

  • Identification data

    Identifier: RP:4405
    Handle: https://hdl.handle.net/20.500.11797/RP4405
    Authors:
    Becerra-Bonache, Leonor
    Abstract:
    The eld of Grammatical Inference provides a good theoretical framework for investigating a learning process. Formal results in this eld can be relevant to the question of rst language acquisition. However, Grammatical Inference studies have been focused mainly on mathematical aspects, and have not exploited the linguistic relevance of their results. With this paper, we try to enrich Grammatical Inference studies with ideas from Linguistics. We propose a non-classical mechanism that has relevant linguistic and computational properties, and we study its learnability from positive data.

  • Others:

    Author, as appears in the article.: Becerra-Bonache, Leonor
    Keywords: language
    Abstract: The eld of Grammatical Inference provides a good theoretical framework for investigating a learning process. Formal results in this eld can be relevant to the question of rst language acquisition. However, Grammatical Inference studies have been focused mainly on mathematical aspects, and have not exploited the linguistic relevance of their results. With this paper, we try to enrich Grammatical Inference studies with ideas from Linguistics. We propose a non-classical mechanism that has relevant linguistic and computational properties, and we study its learnability from positive data.
    Journal publication year: 2012
    Publication Type: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article