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Acquisition of useful lemma-knowledge in automated reasoning

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Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1480))

Abstract

This paper presents a method for solving “hard” problems with automated theorem provers. Main principle is the support of a conventional brute-force search by lemma-knowledge, which is generated and elicitated by the prover system. The performance of the proposed method depends critically on the usefulness of the elicitated lemmata for the actual proof task. In this context an evaluation function called information measure is introduced, which relates the effort required for the production of a lemma f to the problem relevancy of f. Experiments show its high potential.

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Authors and Affiliations

  1. Technische Universität München, D-80290, München, Germany

    Joachim Draeger

Authors
  1. Joachim Draeger
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Fausto Giunchiglia

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© 1998 Springer-Verlag Berlin Heidelberg

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Draeger, J. (1998). Acquisition of useful lemma-knowledge in automated reasoning. In: Giunchiglia, F. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 1998. Lecture Notes in Computer Science, vol 1480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0057448

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  • DOI: https://doi.org/10.1007/BFb0057448

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64993-9

  • Online ISBN: 978-3-540-49793-6

  • eBook Packages: Springer Book Archive

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