Learning formal languages based on control sets

  • Yuji Takada
1 Inductive Inference Theory 1.2 Inductive Inference of Formal Languages
Part of the Lecture Notes in Computer Science book series (LNCS, volume 961)


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    V. Amar and G. Putzolu. On a family of linear grammars. Information and Control, 7:283–291, 1964.Google Scholar
  2. [2]
    D. Angluin. A note on the number of queries needed to identify regular languages. Information and Control, 51:76–87, 1981.Google Scholar
  3. [3]
    D. Angluin. Inference of reversible languages. Journal of the ACM, 29(3):741–765, 1982.Google Scholar
  4. [4]
    D. Angluin. Learning k-bounded context-free grammars. RR 557, YALEU/DCS, 1987.Google Scholar
  5. [5]
    D. Angluin. Learning regular sets from queries and counter-examples. Information and Computation, 75:87–106, 1987.Google Scholar
  6. [6]
    D. Angluin and C. H. Smith. Inductive inference: Theory and methods. ACM Computing Surveys, 15(3):237–269, 1983.Google Scholar
  7. [7]
    J. Dassow and G. Paun. Regulated Rewriting in Formal Language Theory, volume 18 of EATCS Monographs on Theoretical Computer Science. Springer-Verlag, Berlin, 1989.Google Scholar
  8. [8]
    J. Earley. An efficient context-free parsing algorithm. Communications of the ACM, 13(2):94–102, 1970.Google Scholar
  9. [9]
    E. Gold. Language identification in the limit. Information and Control, 10:447–474, 1967.Google Scholar
  10. [10]
    R. C. Gonzalez and M. G. Thomason. Syntactic Pattern Recognition: An Introduction. Addison-Wesley, Reading, Mass., 1978.Google Scholar
  11. [11]
    O. H. Ibarra. Simple matrix languages. Information and Control, 17:359–394, 1970.Google Scholar
  12. [12]
    R. McNaughton. Parenthesis grammars. Journal of the ACM, 14(3):490–500, 1967.Google Scholar
  13. [13]
    L. Pitt. Inductive inference, DFAs, and computational complexity. In K. P. Jantke, editor, Proceedings of 2nd Workshop on Analogical and Inductive Inference, Lecture Notes in Artificial Intelligence, 397, pages 18–44. Springer-Verlag, 1989.Google Scholar
  14. [14]
    V. Radhakrishnan and G. Nagaraja. Inference of even linear grammars and its application to picture description languages. Pattern Recognition, 21(1):55–62, 1988.Google Scholar
  15. [15]
    A. L. Rosenberg. A machine realization of the linear context-free languages. Information and Control, 10:175–188, 1967.Google Scholar
  16. [16]
    Y. Sakakibara. Learning context-free grammars from structural data in polynomial time. Theoretical Computer Science, 76(2):223–242, 1990.Google Scholar
  17. [17]
    Y. Sakakibara. Efficient learning of context-free grammars from positive structural examples. Information and Computation, 97:23–60, 1992.Google Scholar
  18. [18]
    R. Siromoney. On equal matrix languages. Information and Control, 14:135–151, 1969.Google Scholar
  19. [19]
    Y. Takada. Grammatical inference for even linear languages based on control sets. Information Processing Letters, 28(4):193–199, 1988.Google Scholar
  20. [20]
    Y. Takada. Inferring parenthesis linear grammars based on control sets. Journal of Information Processing, 12(1):27–33, 1988.Google Scholar
  21. [21]
    Y. Takada. Learning equal matrix grammars and multitape automata with structural information. In Proceedings of the first Workshop on Algorithmic Learning Theory, 1990.Google Scholar
  22. [22]
    Y. Takada. Learning even equal matrix languages based on control sets. In M. Nivat, editor, Parallel Image Analysis, Lecture Notes in Computer Science, 654 Springer-Verlag, 1992.Google Scholar
  23. [23]
    Y. Takada. A hierarchy of language families learnable by regular language learners. To appear in Second International Colloquium on Grammatical Inference, 1994.Google Scholar
  24. [24]
    Y. Takada. Learning equal matrix grammars based on control sets. To appear in International Journal of Pattern Recognition and Artificial Intelligence, Vol.8, No.2, 1994.Google Scholar
  25. [25]
    L. G. Valiant. A theory of the learnable. Communications of the ACM, 27:1134–1142, 1984.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Yuji Takada
    • 1
  1. 1.Fujitsu Laboratories Ltd.Institute for Social Information Science (ISIS)ShizuokaJapan

Personalised recommendations