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International Conference on Algorithmic Learning Theory

ALT 2005: Algorithmic Learning Theory pp 312–326Cite as

A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3734))

Abstract

In this paper, we study inferability of Prolog programs from positive examples alone. We define a class of Prolog programs called recursion bounded programs that can capture non-linear relationships between inputs and outputs and yet inferable from positive examples. This class is rich enough to include many programs like append, delete, insert, reverse, permute, count, listsum, listproduct, insertion-sort, quick-sort on lists, various tree traversal programs and addition, multiplication, factorial, power on natural numbers. The relation between our results and the known results is also discussed. In particular, the class of recursion bounded programs contains all the known terminating linearly-moded Prolog programs of Krishna Rao [7] and additional programs like power on natural numbers which do not belong to the class of linearly-moded programs and the class of safe programs of Martin and Sharma [12].

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Author information

Authors and Affiliations

  1. Information and Computer Science Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    M. R. K. Krishna Rao

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

Editors and Affiliations

  1. School of Computing, National University of Singapore, 117590, Singapore

    Sanjay Jain

  2. Ruhr-Universität Bochum, Germany

    Hans Ulrich Simon

  3. Department of Information and Communication Engineering, Faculty of Electro-Communications, The University of Electro-Communications, Chofugaoka 1–5–1, Chofu, 182-8585, Tokyo, Japan

    Etsuji Tomita

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Rao, M.R.K.K. (2005). A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data. In: Jain, S., Simon, H.U., Tomita, E. (eds) Algorithmic Learning Theory. ALT 2005. Lecture Notes in Computer Science(), vol 3734. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564089_25

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  • DOI: https://doi.org/10.1007/11564089_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29242-5

  • Online ISBN: 978-3-540-31696-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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