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MAT learners for tree series: an abstract data type and two realizations

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Abstract

We propose abstract observation tables, an abstract data type for learning deterministic weighted tree automata in Angluin’s minimal adequate teacher (MAT) model, and show that every correct implementation of abstract observation tables yields a correct MAT learner. Besides the “classical” observation table, we show that abstract observation tables can also be implemented by observation trees. The advantage of the latter is that they often require fewer queries to the teacher.

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Authors and Affiliations

  1. Department of Computing Science, Umeå University, Umeå, 90187, Sweden

    Frank Drewes & Johanna Högberg

  2. Departament de Filologies Romàniques, Universitat Rovira i Virgili, Av. Catalunya 35, Tarragona, 43002, Spain

    Andreas Maletti

Authors
  1. Frank Drewes
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  2. Johanna Högberg
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  3. Andreas Maletti
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Corresponding author

Correspondence to Frank Drewes.

Additional information

Andreas Maletti is supported by the Ministerio de Educación y Ciencia (MEC) grant JDCI-2007-760.

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Drewes, F., Högberg, J. & Maletti, A. MAT learners for tree series: an abstract data type and two realizations. Acta Informatica 48, 165–189 (2011). https://doi.org/10.1007/s00236-011-0135-x

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  • DOI: https://doi.org/10.1007/s00236-011-0135-x

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