@inproceedings{3406adcbd4fa4ed98c404e6d77410325,
title = "Locality, reversibility, and beyond: Learning languages from positive data",
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.",
keywords = "Approximate learning, Identification in the limit from positive data, Local languages, Regular languages, Reversible languages",
author = "Tom Head and Satoshi Kobayashi and Takashi Yokomori",
year = "1998",
doi = "10.1007/3-540-49730-7_15",
language = "English",
isbn = "354065013X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "191--204",
editor = "Richter, {Michael M.} and Smith, {Carl H.} and Rolf Wiehagen and Thomas Zeugmann",
booktitle = "Algorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings",
note = "9th International Conference on Algorithmic Learning Theory, ALT 1998 ; Conference date: 08-10-1998 Through 10-10-1998",
}