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Overview of the Prodigy Learning Apprentice

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

Abstract

This paper briefly describes the PRODIGY system1, a learning apprentice for robot construction tasks currently being developed at Carnegie-Mellon University. After solving a problem, PRODIGY re-examines the search tree and analyzes its mistakes. By doing so, PRODIGY can often find efficient tests for determining if a problem solving method is applicable. If adequate performance cannot be achieved through analysis alone, PRODIGY can initiate a focused dialogue with a teacher to learn the circumstances under which a problem solving method is appropriate.

Keywords

Search Tree Inference Rule Paper Briefly Solution Sequence Applicability Condition 
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

  • Steven Minton
    • 1
  1. 1.Department of Computer ScienceCarnegie-Mellon UniversityPittsburghUSA

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