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Polynomial Time Identification of Strict Prefix Deterministic Finite State Transducers

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Grammatical Inference: Theoretical Results and Applications (ICGI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6339))

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Abstract

This paper is concerned with a subclass of finite state transducers, called strict prefix deterministic finite state transducers (SPDFST’s for short), and studies a problem of identifying the subclass in the limit from positive data. After providing some properties of languages accepted by SPDFST’s, we show that the class of SPDFST’s is polynomial time identifiable in the limit from positive data in the sense of Yokomori.

This work was supported in part by Grants-in-Aid for Scientific Research Nos. 18500108 and 20500007 from the MEXT of Japan.

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References

  1. Berstel, J.: Transductions and Context-Free Languages. Teubner Studienbücher, Stuttgart (1979)

    Google Scholar 

  2. Oncina, J., García, P., Vidal, E.: Learning subsequential transducers for pattern recognition interpretation tasks. IEEE Trans. on Pattern Analysis and Machine Intelligence 15(5), 448–458 (1993)

    Article  Google Scholar 

  3. Pitt, L.: Inductive inference, DFAs, and computational complexity. In: Jantke, K.P. (ed.) AII 1989. LNCS (LNAI), vol. 397, pp. 18–44. Springer, Heidelberg (1989)

    Google Scholar 

  4. Yokomori, T.: On polynomial-time learnability in the limit of strictly deterministic automata. Machine Learning 19, 153–179 (1995)

    MATH  Google Scholar 

  5. Yokomori, T.: Polynomial-time identification of very simple grammars from positive data. Theoretical Computer Science 298, 179–206 (2003)

    Article  MATH  MathSciNet  Google Scholar 

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Wakatsuki, M., Tomita, E. (2010). Polynomial Time Identification of Strict Prefix Deterministic Finite State Transducers. In: Sempere, J.M., García, P. (eds) Grammatical Inference: Theoretical Results and Applications. ICGI 2010. Lecture Notes in Computer Science(), vol 6339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15488-1_34

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  • DOI: https://doi.org/10.1007/978-3-642-15488-1_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15487-4

  • Online ISBN: 978-3-642-15488-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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