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

Tom Head, Satoshi Kobayashi, Takashi Yokomori

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルAlgorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings
編集者Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann
出版社Springer Verlag
ページ191-204
ページ数14
ISBN(印刷版)354065013X, 9783540650133
DOI
出版ステータスPublished - 1998
イベント9th International Conference on Algorithmic Learning Theory, ALT 1998 - Otzenhausen, Germany
継続期間: 1998 10 81998 10 10

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
1501
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

フィンガープリント 「Locality, reversibility, and beyond: Learning languages from positive data」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル