BiographyAndreas Schlaginhaufen received his Bachelor and Master Degree in Electrical Engineering and Information Technology from ETH Zurich, Switzerland. Furthermore, he studied for an exchange semester at the University of Toronto, Canada. He interned in the power grid development team of EWZ Zurich, as well as in the learning & adaptive systems group at ETH Zurich. In his master thesis he investigated stable deep dynamics models for partially observed or time-delayed dynamical systems. His current research interests are centered around safety aspects in reinforcement learning, learning from human demonstrations, and learning in multiagent systems.
|Andreas Schlaginhaufen, Maryam Kamgarpour
Proceedings of the 40th International Conference on Machine Learning
|Identifiability and Generalizability in Constrained Inverse Reinforcement Learning|
|Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler
Advances in Neural Information Processing Systems 34 (NeurIPS 2021)
|Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems|