Abstract : Adaptation is a task of case-based reasoning systems that is largely domain-dependant. This motivates the study of adaptation knowledge acquisition (AKA) that can be carried out thanks to learning processes on the variations between cases of the case base. This paper studies the representation of these variations and the impact of this representation on the AKA process, through experiments in an oncology domain.
https://hal.inria.fr/inria-00337554
Contributor : Fadi Badra
<>
Submitted on : Thursday, August 27, 2009 - 5:38:06 PM
Last modification on : Friday, May 24, 2019 - 10:56:07 AM
Long-term archiving on : Monday, June 7, 2010 - 10:48:28 PM
Fadi Badra, Jean Lieber. Representing Case Variations for Learning General and Specific Adaptation Rules. Fourth Starting AI Researcher's Symposium (STAIRS 2008), Jul 2008, Patras, Greece. pp.1--11. ⟨inria-00337554⟩
