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Learning Left-to-Right and Right-to-Left Iterative Languages

  • Jeffrey Heinz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5278)

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).

Keywords

Regular Expression Regular Language Positive Data Language Class Sound Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jeffrey Heinz
    • 1
  1. 1.University of DelawareNewarkUSA

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