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International Workshop on Algorithmic Learning Theory

ALT 1993: Algorithmic Learning Theory pp 101–110Cite as

Inductive resolution

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 744))

Abstract

A clausal system IDR for inductive inference is proposed. Given back-ground knowledge ß and an observed fact B, each represented in terms of clauses, it infers a set H of clauses such that ß ∪ H⊢ O. It is inductively complete, i.e., can find every possible H regardless of whether O = □ or not. When hypothesis generation is suppressed, it simulates OL-deduction

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Author information

Authors and Affiliations

  1. Electrotechnical Laboratory, 1-1-4 Umezono Tsukuba, 305, Ibaraki, Japan

    Taisuke Sato & Sumitaka Akiba

Authors
  1. Taisuke Sato
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  2. Sumitaka Akiba
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Editor information

Klaus P. Jantke Shigenobu Kobayashi Etsuji Tomita Takashi Yokomori

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© 1993 Springer-Verlag Berlin Heidelberg

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Sato, T., Akiba, S. (1993). Inductive resolution. In: Jantke, K.P., Kobayashi, S., Tomita, E., Yokomori, T. (eds) Algorithmic Learning Theory. ALT 1993. Lecture Notes in Computer Science, vol 744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57370-4_40

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  • DOI: https://doi.org/10.1007/3-540-57370-4_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57370-8

  • Online ISBN: 978-3-540-48096-9

  • eBook Packages: Springer Book Archive

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