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Grammatical inference: An old and new paradigm

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Algorithmic Learning Theory (ALT 1995)

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

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Abstract

In this paper, we provide a survey of recent advances in the field “grammatical inference” with a particular emphasis on the results concerning the learnability of target classes represented by deterministic finite automata, context-free grammars, hidden Markov models, stochastic context-free grammars, simple recurrent neural networks, and casebased representations.

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Authors and Affiliations

  1. Fujitsu Laboratories Ltd., Institute for Social Information Science, 140, Miyamoto, Numazu, 410-03, Shizuoka, Japan

    Yasubumi Sakakibara

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  1. Yasubumi Sakakibara
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Klaus P. Jantke Takeshi Shinohara Thomas Zeugmann

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Sakakibara, Y. (1995). Grammatical inference: An old and new paradigm. 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_25

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  • DOI: https://doi.org/10.1007/3-540-60454-5_25

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  • Print ISBN: 978-3-540-60454-9

  • Online ISBN: 978-3-540-47470-8

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