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Learning Logic Programs with Local Variables from Positive Examples

  • M. R. K. Krishna Rao
  • Abdul Sattar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1747)

Abstract

We present a polynomial time algorithm to learn a rich class of logic programs (called one-recursive programs) from positive examples alone. This class of programs uses the divide-and-conquer methodology and contains a wide range of programs such as append, reverse, merge, split, delete, insertion-sort, preorder and inorder traversal of binary trees, polynomial recognition, derivatives, sum of a list of numbers and allows local variables.

Keywords

Local Variable Logic Program Polynomial Time Algorithm Positive Data Unit Clause 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    H. Arimura, H. Ishizaka and T. Shinohara (1992), Polynomial time inference of a subclass of context-free transformations, Proc. of COLT’92, pp. 136–143.Google Scholar
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    M.R.K. Krishna Rao (1996), A class of Prolog programs inferable from positive data, Proc. of ALT’96, Lecture Notes in Computer Science 1160, pp. 272–84.Google Scholar
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    M.R.K. Krishna Rao and A. Sattar (1999), Learning logic programs with local variables from positive examples, Technical Report, Griffith University.Google Scholar
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    L. Sterling and E. Shapiro (1994), The Art of Prolog, MIT Press.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • M. R. K. Krishna Rao
    • 1
    • 2
  • Abdul Sattar
    • 1
    • 2
  1. 1.Computer Science DepartmentJames Cook UniversityTownsvilleAustralia
  2. 2.School of Computing and Information TechnologyGriffith UniversityNathan, BrisbaneAustralia

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