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Abstract: The case-based reasoning paradigm models how reuse of stored experiences contributes to expertise. In a case-based problem-solver, new problems are solved by retrieving stored information about previous problem-solving episodes and adapting it to suggest solutions to the new problems. The results are then themselves added to the reasoner's memory in new cases for future use. Despite this emphasis on learning from experience, however, experience generally plays a minimal role in models of how... (Update)
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2.5: CBR in Context: The Present and Future - Leake (1996) (Correct)
1.7: Becoming An Expert Case-Based Reasoner: Learning To Adapt Prior.. - Leake (1995) (Correct)
1.5: Learning to Improve Case Adaptation by Introspective.. - Leake, Kinley, Wilson (1995) (Correct)
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BibTeX entry: (Update)
@misc{ leake-experience,
author = "David B. Leake",
title = "Experience, Introspection, and Expertise: Learning to Refine the Case-Based
Reasoning Process",
url = "citeseer.ist.psu.edu/1595.html" }
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Documents on the same site (http://fermivista.math.jussieu.fr/ftp/ftp.cs.indiana.edu.html): More
Modeling Case-based Planning for Repairing Reasoning Failures - Fox, Leake (1995) (Correct)
Transfer in a Connectionist Model of the Acquisition of Morphology - Gasser (1995) (Correct)
Pict: A Programming Language Based on the Pi-Calculus - Pierce, Turner (1997) (Correct)
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