Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Agents must form and update mental models about each other in a wide range of domains: team coordination, plan recognition, social simulation, user modeling, games of incomplete i...
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Composition of requirements models in Software Product Line (SPL) development enables stakeholders to derive the requirements of target software products and, very important, to re...
The complexity of engineers tasks leads us to provide means to bring the Adaptive Multi-Agent Systems (AMAS) design to a higher stage of automation and confidence thanks to Model D...
Sylvain Rougemaille, Jean-Paul Arcangeli, Marie Pi...