This project will synergistically analyze transformations from model based diagnosis to exhibit fault indicators and data transformations from data based diagnosis methods.

The first objective is to highlight and understand the correspondences that may exist between them and how they could complement each other.

The second objective is to be able to abstract up data configurations and map them to models suitable for diagnosis reasoning.

Programmmes : IA acceptable, certifiable & collaborative
Thèmes : Raisonnement automatique et décision, explicabilité, données et anomalies

Porteur :
Louise Travé-Messuyes, DR CNRS, LAAS