A Case-Based Reasoner Adaptive to Different
Cognitive Tasks

Isabelle Bichindaritz

Universit Ren Descartes, LIAP-5, UFR de Math-Info
45 rue des Saints-Pres, 75270 Paris Cedex 6, France
Email : bici@math-info.univ-paris5.fr


Abstract. Case-based reasoning systems are generally devoted to the
realization of a single cognitive task. The need for such systems to perform 
various cognitive tasks questions how to organize their memory
to permit them to be task-adaptive. The case-based reasoning system
adaptive to cognitive tasks presented here is capable to adapt to analysis
tasks as well as synthesis tasks. Its adaptability comes from its memory
composition, both cases and concepts, and from its hierarchical memory
organization, based on multiple points of view, some of them associated
to the various cognitive tasks it performs. For analytic tasks, the most
specific cases are preferably used for the reasoning process. For synthesis 
tasks, the most specific concepts, learnt by conceptual clustering, are
used. An example of this system abilities, in the domain of eating disorders 
in psychiatry, is briefly presented.
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