Abstract
This research project aims to design new sequential decision-making systems, operating in uncertain environments under multiple conflicting optimization criteria. It is assumed that the dynamics of the system under control (in discrete time and over a finite horizon) is linear and that the exogenous uncertainty can be estimated by parametric probabilistic models. In this context, four cha…