It means that the central issue concerns the selection of one ore several relevant hypotheses, able to best explain a given set of observations. We adopt an artificial intelligence perspective. Respecting this objective assumes the generation of easily interpretable results, and thus to work with conceptually simple models. As real time monitoring is expected, models are exploited off-line for chronicle acquisition or building of a diagnostic automaton called diagnoser. We focus on dynamic systems.
Main topics are abductive reasoning, chronicles learning, diagnoser building.
We study the modeling of text contents through the modeling of the semantic of the elements that form their descriptors in automatic indexing. Contacts and collaborations with universities of Potsdam, Lisbon, and the Beijing mathematical institute.