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Language learning from membership queries and characteristic examples

  • Hiroshi Sakamoto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 997)

Abstract

This paper introduces the notion of characteristic examples and shows that the notion contributes to language learning in polynomial time. A characteristic example of a language L is an element of L which includes, in a sense, sufficient information to represent L. Every context-free language can be divided into a finite number of languages each of which has a characteristic example and it is decidable whether or not a context-free language has a characteristic example. We present an algorithm that learns parenthesis languages using membership queries and characteristic examples. Our algorithm runs in time polynomial in the number of production rules of a minimal parenthesis grammar and in the length of the longest characteristic example.

Keywords

Internal Node Production Rule Target Language Derivation Tree Tree Automaton 
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 1995

Authors and Affiliations

  • Hiroshi Sakamoto
    • 1
  1. 1.Research Institute of Fundamental Information ScienceKyushu University 33FukuokaJapan

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