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Case-based planning to learn

  • J. William Murdock
  • Gordon Shippey
  • Ashwin Ram
Scientific Papers Learning
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1266)

Abstract

Learning can be viewed as a problem of planning a series of modifications to memory. We adopt this view of learning and propose the applicability of the case-based planning methodology to the task of planning to learn. We argue that relatively simple, fine-grained primitive inferential operators are needed to support flexible planning. We show that it is possible to obtain the benefits of case-based reasoning within a planning to learn framework.

Keywords

Adaptation Strategy Knowledge Element Mental Domain Bradford Book Plan Transformation 
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 1997

Authors and Affiliations

  • J. William Murdock
    • 1
  • Gordon Shippey
    • 1
  • Ashwin Ram
    • 1
  1. 1.College of ComputingGeorgia Institute of TechnologyAtlanta

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