Locality, reversibility, and beyond: Learning languages from positive data

Tom Head, Satoshi Kobayashi, Takashi Yokomori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

In algorithmic learning theory fundamental roles are played by the family of languages that are locally testable in the strict sense and by the family of reversible languages. These two families are shown to be the first two members of an infinite sequence of families of regular languages the members of which are learnable in the limit from positive data only. A uniform procedure is given for deciding, for each regular language R and each of our specified families, whether R belongs to the family. The approximation of arbitrary regular languages by languages belonging to these families is discussed. Further, we will give a uniform scheme for learning these families from positive data. Several research problems are also suggested.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings
EditorsMichael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann
PublisherSpringer Verlag
Pages191-204
Number of pages14
ISBN (Print)354065013X, 9783540650133
DOIs
Publication statusPublished - 1998
Event9th International Conference on Algorithmic Learning Theory, ALT 1998 - Otzenhausen, Germany
Duration: 1998 Oct 81998 Oct 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1501
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Algorithmic Learning Theory, ALT 1998
CountryGermany
CityOtzenhausen
Period98/10/898/10/10

Keywords

  • Approximate learning
  • Identification in the limit from positive data
  • Local languages
  • Regular languages
  • Reversible languages

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Head, T., Kobayashi, S., & Yokomori, T. (1998). Locality, reversibility, and beyond: Learning languages from positive data. In M. M. Richter, C. H. Smith, R. Wiehagen, & T. Zeugmann (Eds.), Algorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings (pp. 191-204). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1501). Springer Verlag. https://doi.org/10.1007/3-540-49730-7_15