Analogical logic program synthesis from examples

  • Ken Sadohara
  • Makoto Haraguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 912)


The purpose of this paper is to present a theory and an algorithm for analogical logic program synthesis from examples. Given a source program and examples, the task of our algorithm is to find a program which explains the examples correctly and is similar to the source program. Although we can define a notion of similarity in various ways, we consider a class of similarities from the viewpoint of how examples are explained by a program. In a word, two programs are said to be similar if they share a common explanation structure at an abstract level. Using this notion of similarity, we formalize an analogical logic program synthesis and show that our algorithm based on a framework of model inference can identify a desired program.


Logic Program Function Symbol Predicate Symbol Inductive Logic Programming Source Program 
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 1995

Authors and Affiliations

  • Ken Sadohara
    • 1
  • Makoto Haraguchi
    • 1
  1. 1.Department of Systems ScienceTokyo Institute of TechnologyYokohamaJapan

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