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Learning from Entailment of Logic Programs with Local Variables

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Algorithmic Learning Theory (ALT 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1501))

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Abstract

In this paper, we study exact learning of logic programs from entailment and present a polynomial time algorithm to learn a rich class of logic programs that allow local variables and include many standard programs like append, merge, split, delete, member, prefix, suffix, length, reverse, append/4 on lists, tree traversal programs on binary trees and addition, multiplication, exponentiation on natural numbers. Grafting a few aspects of incremental learning [9] onto the framework of learning from entailment [3], we generalize the existing results to allow local variables, which play an important role of sideways information passing in the paradigm of logic programming.

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© 1998 Springer-Verlag Berlin Heidelberg

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Krishna Rao, M.R.K., Sattar, A. (1998). Learning from Entailment of Logic Programs with Local Variables. In: Richter, M.M., Smith, C.H., Wiehagen, R., Zeugmann, T. (eds) Algorithmic Learning Theory. ALT 1998. Lecture Notes in Computer Science(), vol 1501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49730-7_11

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  • DOI: https://doi.org/10.1007/3-540-49730-7_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65013-3

  • Online ISBN: 978-3-540-49730-1

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