Learning approximately regular languages with reversible languages

Satoshi Kobayashi; Takashi Yokomori

doi:10.1016/S0304-3975(96)00224-1

Learning approximately regular languages with reversible languages

Satoshi Kobayashi^*, Takashi Yokomori

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

27 Citations (Scopus)

Abstract

In this note, we consider the problem of learning approximately regular languages in the limit from positive data using the class of k-reversible languages. The class of k-reversible languages was introduced by Angluin (1982), and proved to be efficiently identifiable in the limit from positive data only. We show that Angluin's learning algorithm for the class of k-reversible languages can be readily adopted for the approximate identification of regular languages from positive data. Considering the negative result on the exact identifiability by Gold (1967), this approximation approach would be one of the best we could hope for learning the class of regular languages from positive data only.

Original language	English
Pages (from-to)	251-257
Number of pages	7
Journal	Theoretical Computer Science
Volume	174
Issue number	1-2
DOIs	https://doi.org/10.1016/S0304-3975(96)00224-1
Publication status	Published - 1997 Mar 15
Externally published	Yes

Keywords

Approximate learning
Computational learning theory
Formal language theory
Identification in the limit

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1016/S0304-3975(96)00224-1

Cite this

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title = "Learning approximately regular languages with reversible languages",

abstract = "In this note, we consider the problem of learning approximately regular languages in the limit from positive data using the class of k-reversible languages. The class of k-reversible languages was introduced by Angluin (1982), and proved to be efficiently identifiable in the limit from positive data only. We show that Angluin's learning algorithm for the class of k-reversible languages can be readily adopted for the approximate identification of regular languages from positive data. Considering the negative result on the exact identifiability by Gold (1967), this approximation approach would be one of the best we could hope for learning the class of regular languages from positive data only.",

keywords = "Approximate learning, Computational learning theory, Formal language theory, Identification in the limit",

author = "Satoshi Kobayashi and Takashi Yokomori",

note = "Funding Information: We are grateful to the anonymous referees for valuable comments to improve the quality of this note. This work was supported in part by Grants-in-Aid for Scientific ResearchN o. 07780310( for the first author) and No. 07249201( for the second author) from the Ministry of Education, Science and Culture, Japan.",

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doi = "10.1016/S0304-3975(96)00224-1",

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T1 - Learning approximately regular languages with reversible languages

AU - Kobayashi, Satoshi

AU - Yokomori, Takashi

N1 - Funding Information: We are grateful to the anonymous referees for valuable comments to improve the quality of this note. This work was supported in part by Grants-in-Aid for Scientific ResearchN o. 07780310( for the first author) and No. 07249201( for the second author) from the Ministry of Education, Science and Culture, Japan.

PY - 1997/3/15

Y1 - 1997/3/15

N2 - In this note, we consider the problem of learning approximately regular languages in the limit from positive data using the class of k-reversible languages. The class of k-reversible languages was introduced by Angluin (1982), and proved to be efficiently identifiable in the limit from positive data only. We show that Angluin's learning algorithm for the class of k-reversible languages can be readily adopted for the approximate identification of regular languages from positive data. Considering the negative result on the exact identifiability by Gold (1967), this approximation approach would be one of the best we could hope for learning the class of regular languages from positive data only.

AB - In this note, we consider the problem of learning approximately regular languages in the limit from positive data using the class of k-reversible languages. The class of k-reversible languages was introduced by Angluin (1982), and proved to be efficiently identifiable in the limit from positive data only. We show that Angluin's learning algorithm for the class of k-reversible languages can be readily adopted for the approximate identification of regular languages from positive data. Considering the negative result on the exact identifiability by Gold (1967), this approximation approach would be one of the best we could hope for learning the class of regular languages from positive data only.

KW - Approximate learning

KW - Computational learning theory

KW - Formal language theory

KW - Identification in the limit

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Learning approximately regular languages with reversible languages

Abstract

Keywords

ASJC Scopus subject areas

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