Skip to main content
Log in

Learning two-tape automata from queries and counterexamples

  • Published:
Mathematical systems theory Aims and scope Submit manuscript

Abstract

We investigate the learning problem of two-tape deterministic finite automata (2-tape DFAs) from queries and counterexamples. Instead of accepting a subset of ∑*, a 2-tape DFA over an alphabet ∑ accepts a subset of ∑* × ∑*, and therefore, it can specify a binary relation on ∑*. In [3] Angluin showed that the class of deterministic finite automata (DFAs) is learnable in polynomial time from membership queries and equivalence queries, namely, from a minimally adequate teacher (MAT).

In this article we show that the class of 2-tape DFAs is learnable in polynomial time from MAT. More specifically, we show an algorithm that, given any languageL accepted by an unknown 2-tape DFAM, learns from MAT a two-tape nonde-terministic finite automaton (2-tape NFA)M′ acceptingL in time polynomial inn andl, wheren is the size ofM andl is the maximum length of any counterexample provided during the learning process.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. V. Amar and G. Putzolu. Generalizations of regular events.Information and Control, 8:56–63, 1965.

    Article  MathSciNet  MATH  Google Scholar 

  2. D. Angluin. Learningk-bounded context-free grammars. Research Report 557, Department of Computer Science, Yale University, 1987.

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

    Article  MATH  MathSciNet  Google Scholar 

  4. D. Angluin and D. N. Hoover. Regular prefix relations.Mathematical Systems Theory, 17:167–191, 1984.

    Article  MATH  MathSciNet  Google Scholar 

  5. D. Angluin and M. Kharitonov. When won't membership queries help?Proceedings of the 23ndACM Symposium on Theory of Computing, pages 444–454, 1991.

  6. P. Berman and R. Roos. Learning one-counter languages in polynomial time.Proceedings of the 28th IEEE Symposium on Foundations of Computer Science, pages 61–67, 1987.

  7. W. Brauer and K.-J. Lange. Non-deterministic two-tape automata are more powerful than deterministic ones.Proceedings of the 2nd Annual Symposium on Theoretical Aspects of Computer Science, pages 71–79. Lecture Notes in Computer Science, Vol. 182. Springer-Verlag, Berlin, 1985.

    Google Scholar 

  8. S. Eilenberg, C. C. Elgot and J. C. Shepherdson. Sets recognized byn-tape automata.Journal of Algebra, 13:447–464, 1969.

    Article  MATH  MathSciNet  Google Scholar 

  9. C. C. Elgot and J. E. Mezei. On relations defined by generalized finite automata.IBM Journal of Research and Development, 9:47–68, 1965.

    Article  MATH  MathSciNet  Google Scholar 

  10. S. Ginsburg.Algebraic and Automata-Theoretic Properties of Formal Languages. North-Holland, Amsterdam, 1975.

    MATH  Google Scholar 

  11. S. A. Goldman, R. L. Rivest, and R. E. Schapire. Learning binary relations and total orders.Proceedings of the 30th IEEE Symposium on Foundations of Computer Science, pages 46–51, 1989.

  12. J. N. Gray and M. A. Harrison. The theory of sequential relations.Information and Control, 9:435–468, 1966.

    Article  MATH  MathSciNet  Google Scholar 

  13. M. A. Harrison.Introduction to Formal Language Theory. Addison-Wesley, Reading, MA, 1978.

    MATH  Google Scholar 

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

    Google Scholar 

  15. M. Rabin and D. Scott. Finite automata and their decision problem.IBM Journal of Research and Development, 3:114–125, 1959.

    MathSciNet  Google Scholar 

  16. A. L. Rozenberg. A machine realization of the linear context-free languages.Information and Control, 10:175–188, 1967.

    Article  MathSciNet  Google Scholar 

  17. E. Shapiro. Inductive inference of theories from facts. Research Report 192, Department of Computer Science, Yale University, 1981.

  18. H. Shirakawa and T. Yokomori. Polynomial-time MAT learning of C-deterministic context-free grammars.Transactions of the Information Processing Society of Japan, 34(3):380–390, 1993.

    Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  20. T. Yokomori. Learning non-deterministic finite automata from queries and counterexamples. InMachine Intelligence, Vol. 13 (Furukawa, Michie and Muggleton, eds.), Oxford University Press, Oxford, pages 169–189, 1994.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

This work was supported in part by Grants-in-Aid for Scientific Research No. 04229105 from the Ministry of Education, Science, and Culture, Japan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yokomori, T. Learning two-tape automata from queries and counterexamples. Math. Systems Theory 29, 259–270 (1996). https://doi.org/10.1007/BF01201279

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01201279

Keywords

Navigation