Learning by Understanding Analogies

  • Russell Greiner
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 12)


This research describes a method for learning by analogy — i.e., for proposing new conjectures about a target analogue based on facts known about a source analogue. We formalize this process as a rule of plausible inference and present heuristics which guide this process towards efficiently postulating useful new conjectures. The most important rule involves the use of abstractions — abstract relations that encode solution methods to past problems.


Analogical Inference Plausible Inference Source Analogue Past Problem Target Analogue 
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

© Kluwer Academic Publishers 1986

Authors and Affiliations

  • Russell Greiner
    • 1
  1. 1.Knowledge Systems LaboratoryStanford UniversityUSA

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