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Learning Multiplicity Tree Automata

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Grammatical Inference: Algorithms and Applications (ICGI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4201))

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Abstract

In this paper, we present a theoretical approach for the problem of learning multiplicity tree automata. These automata allows one to define functions which compute a number for each tree. They can be seen as a strict generalization of stochastic tree automata since they allow to define functions over any field K. A multiplicity automaton admits a support which is a non deterministic automaton. From a grammatical inference point of view, this paper presents a contribution which is original due to the combination of two important aspects. This is the first time, as far as we now, that a learning method focuses on non deterministic tree automata which computes functions over a field. The algorithm proposed in this paper stands in Angluin’s exact model where a learner is allowed to use membership and equivalence queries. We show that this algorithm is polynomial in time in function of the size of the representation.

This work was supported in part by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. This publication only reflects the authors’ views.

This work is part of the ARA marmota french projet.

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Author information

Authors and Affiliations

  1. LIF – Université de Provence, 39, rue Frédéric Joliot Curie, 13453 cedex 13, Marseille, France

    Amaury Habrard

  2. Dep. de Lenguajes y Sistemas Informático, Universidad de Alicante, E-03071, Alicante, Spain

    Jose Oncina

Authors
  1. Amaury Habrard
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  2. Jose Oncina
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Editor information

Editors and Affiliations

  1. Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, 223-8522, Yokohama, Japan

    Yasubumi Sakakibara

  2. Dept. of Computer Science, Kyoto Sangyo University, Kamigamo Motoyama, Kita-ku, Kyoto, Japan

    Satoshi Kobayashi

  3. Japan Biological Informatics Consortium, 10F TIME24 Building, 2-45 Aomi, Koto-ku, 135-8073, Tokyo, Japan

    Kengo Sato

  4. Department of Information and Communication Engineering, Graduate School of Electro-Communications, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu-shi, 182-8585, Tokyo, Japan

    Tetsuro Nishino

  5. Department of Information and Communication Engineering, Faculty of Electro-Communications, The University of Electro-Communications, Chofugaoka 1–5–1, Chofu, 182-8585, Tokyo, Japan

    Etsuji Tomita

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© 2006 Springer-Verlag Berlin Heidelberg

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Habrard, A., Oncina, J. (2006). Learning Multiplicity Tree Automata . In: Sakakibara, Y., Kobayashi, S., Sato, K., Nishino, T., Tomita, E. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2006. Lecture Notes in Computer Science(), vol 4201. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11872436_22

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  • DOI: https://doi.org/10.1007/11872436_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45264-5

  • Online ISBN: 978-3-540-45265-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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