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Inductive Inference of Term Rewriting Systems from Positive Data

  • M. R. K. Krishna Rao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3244)

Abstract

In this paper, we study inferability of term rewriting systems from positive examples alone. We define a class of simple flat term rewriting systems that are inferable from positive examples. In flat term rewriting systems, nesting of defined symbols is forbidden in both left- and right-hand sides. A flat TRS is simple if the size of redexes in the right-hand sides is bounded by the size of the corresponding left-hand sides. The class of simple flat TRSs is rich enough to include many divide-and-conquer programs like addition, doubling, tree-count, list-count, split, append, etc. The relation between our results and the known results on Prolog programs is also discussed. In particular, flat TRSs can define functions (like doubling), whose output is bigger in size than the input, which is not possible with linearly-moded Prolog programs.

Keywords

Function Symbol Inductive Inference Positive Data Semantic Mapping Pattern Language 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • M. R. K. Krishna Rao
    • 1
  1. 1.Information and Computer Science DepartmentKing Fahd University of Petroleum and MineralsDhahranSaudi Arabia

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