Skip to main content

Language learning from membership queries and characteristic examples

  • Conference paper
  • First Online:
Algorithmic Learning Theory (ALT 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 997))

Included in the following conference series:

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dana Angluin. Queries and concept learning. Machine Learning, 2:319–342, 1988.

    Google Scholar 

  2. Dana Angluin. Learning k-bounded context-free grammars. Technical Report YALEU/DCS/RR-557, Department of Computer Science, Yale University, 1987.

    Google Scholar 

  3. Dana Angluin. Learning regular sets from queries and counterexamples. Information and Computation, 75:87–106, 1987.

    Article  Google Scholar 

  4. Dana Angluin. A note on the number of queries needed to identify regular languages. Information and Control, 51:76–87, 1981.

    Article  Google Scholar 

  5. Piotr Berman and Pobert Roos. Learning one-counter languages in polynomial time. Proceedings of 28th IEEE Symposium on Foundations of Computer Science, pages 61–67. IEEE Computer Society Press, 1987.

    Google Scholar 

  6. Michael A. Harrison. Introduction to Formal Language Theory. Reading, MA:Addison-Wesley, 1978.

    Google Scholar 

  7. Hiroki Ishizaka. Polynomial time learnability of simple deterministic languages. Machine Learning, 5:151–164, 1990.

    Google Scholar 

  8. Donald E. Knuth. Characterization of Parenthesis Languages. Information and Control, 11:269–289, 1967.

    Article  Google Scholar 

  9. Robert McNaughton. Parenthesis Grammars. Journal of the ACM, 14:490–500, 1967.

    Google Scholar 

  10. Yasubumi Sakakibara. Learning context-free grammars from structural data in polynomial time. Theoretical Computer Science, 76:223–242, 1990.

    Google Scholar 

  11. Ehud Y. Shapiro. Algorithmic program debugging. Cambridge, MA: MIT Press, 1983.

    Google Scholar 

  12. Yuji Takada. Grammatical inference for even linear languages based on control sets. Information Processing Letters, 28:193–199, 1988.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Klaus P. Jantke Takeshi Shinohara Thomas Zeugmann

Rights and permissions

Reprints and permissions

Copyright information

© 1995 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Sakamoto, H. (1995). Language learning from membership queries and characteristic examples. In: Jantke, K.P., Shinohara, T., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 1995. Lecture Notes in Computer Science, vol 997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60454-5_28

Download citation

  • DOI: https://doi.org/10.1007/3-540-60454-5_28

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60454-9

  • Online ISBN: 978-3-540-47470-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics