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Abstraction-Based Analogical Inference

  • Russell Greiner
Chapter
Part of the Synthese Library book series (SYLI, volume 197)

Abstract

Designing a system capable of learning new facts has long been a central theme for the general field of Artificial Intelligence; it has also been one of its greatest challenges (Feigenbaum, 1963). This chapter discusses the task of learning by understanding an analogy, describing how to use information about some well understood source analogue as a framework for proposing new conjectures about a target concept.

Keywords

Atomic Formula Target Problem Initial Theory Analogy Formula Cognitive Science Society 
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 Science+Business Media Dordrecht 1988

Authors and Affiliations

  • Russell Greiner
    • 1
  1. 1.Department of Computer ScienceUniversity of TorontoTorontoCanada

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