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Learning left-to-right and right-to-left iterative languages

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

The left-to-right and right-to-left iterative languages are previously unnoticed subclasses of the regular languages of infinite size that are identifiable in the limit from positive data. Essentially, these language classes are the ones obtained by merging final states in a prefix tree and initial states in a suffix tree of the observed sample, respectively. Strikingly, these classes are also transparently related to the zero-reversible languages because some algorithms that learn them differ minimally from the ZR algorithm given in Angluin (1982). Second, they are part of the answer to the challenge provided by Muggleton (1990), who proposed mapping the space of language classes obtainable by a general state-merging algorithm IM1. Third, these classes are relevant to a hypothesis of how children can acquire sound patterns of their language-in particular, the hypothesis that all phonotactic patterns found in natural language are neighborhood-distinct (Heinz 2007).

Original languageEnglish
Title of host publicationGrammatical Inference
Subtitle of host publicationAlgorithms and Applications - 9th International Colloquium, ICGI 2008, Proceedings
Pages84-97
Number of pages14
DOIs
StatePublished - 2008
Event9th International Colloquium on Grammatical Inference, ICGI 2008 - Saint-Malo, France
Duration: Sep 22 2008Sep 24 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5278 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Colloquium on Grammatical Inference, ICGI 2008
Country/TerritoryFrance
CitySaint-Malo
Period09/22/0809/24/08

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