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International Workshop on Algorithmic Learning Theory

ALT 1995: Algorithmic Learning Theory pp 95–109Cite as

Incremental learning of logic programs

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

Abstract

In this paper, we identify a class of polynomial-time learnable logic programs. These programs can be learned from examples in an incremental fashion using the already defined predicates as background knowledge. Our class properly contains the class of innermost simple programs of [20] and the class of hereditary programs of [12,13]. Standard programs for multiplication, quick-sort, reverse and merge are a few examples of programs that can be handled by our results but not by the earlier results of [12, 13, 20].

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Author information

Authors and Affiliations

  1. Computer Science Group, Tata Institute of Fundamental Research, 400 005, Colaba, Bombay, India

    M. R. K. Krishna Rao

  2. Max-Planck-Institut für Informatik Im Stadtwald, 66123, Saarbrücken, Germany

    M. R. K. Krishna Rao

Authors
  1. M. R. K. Krishna Rao
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Editor information

Klaus P. Jantke Takeshi Shinohara Thomas Zeugmann

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© 1995 Springer-Verlag Berlin Heidelberg

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Rao, M.R.K.K. (1995). Incremental learning of logic programs. 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_31

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  • DOI: https://doi.org/10.1007/3-540-60454-5_31

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60454-9

  • Online ISBN: 978-3-540-47470-8

  • eBook Packages: Springer Book Archive

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