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Summary: Published in ECAI-90, Proceedings of the 9th European Conference on Artificial Intelligence, edited by Luigia Aiello, Stockholm, August,
6-10,1990. Pitman Publishing, London, 1990. Pages 1-6.
1
Knowledge-Intensive Case-Based Reasoning
and Sustained Learning
Agnar Aamodt
Knowledge Engineering Laboratory, ELAB-RUNIT, SINTEF
N-7034 Trondheim-NTH, Norway
and
Department of Electrical Engineering and Computer Science
University of Trondheim.
agnar.aamodt@elab-runit.sintef.no
Abstract
In case-based reasoning (CBR) a problem is solved by matching the
problem description to a previously solved case, using the past solution
in solving the new problem. A case-based reasoner learns after each
problem solving session by retaining relevant information from a
problem just solved, making the new experience available for future
problem solving. Crucial steps in a CBR process include finding a good
match to a new problem, adapting a previous solution to successfully
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