A Language of Case Differences
Résumé
This paper contributes to a line of research that consists in applying qualitative reasoning techniques to the formalization of the case-based inference, and in particular, to its adaptation phase. The importance of capturing case differences has long been acknowledged in adaptation research, but research is still needed to properly represent and reason upon case differences. Assuming that case differences can be expressed as a set of feature differences, we show that Category Theory can be used as a mathematical framework to design a qualitative language in which both case differences, similarity paths and adaptation rules can be represented and reasoned upon symbolically.
Domaines
Intelligence artificielle [cs.AI]
Origine : Fichiers produits par l'(les) auteur(s)