ALeSCo (https://alesco.uni-hannover.de) is a new research unit funded by the German Resarch Foundation (DFG) and aims to devise fundamentally new approaches to active learning for dynamical systems and their control, where the learning process is deliberately incentivized or triggered rather than passively relying on pre-collected data. Central questions concern what to learn (system models, controllers), when to learn (depending on suitable data-informativity and performance measures), and how to learn (selecting a suitable learning technique).
ALeSCo's principal investigators are expert control researchers from all over Germany: Matthias Müller (Leibniz University Hannover, spokesperson), Moritz Diehl (University of Freiburg), Sandra Hirche (Technical University of Munich), Timm Faulwasser (Hamburg University of Technology), and Karl Worthmann (Technische Universität Ilmenau). The research unit consists of six individual projects that cover topics from data-informativity, over modeling and control with neural networks, Gaussian Processes, or evolution operators to numerical optimization and benchmarking:
All projects are now hiring — please visit the project website for contact data. Reviewing the applications starts at July 10 until the positions are filled.
