24 citations · 42 across the 3 of their papers we have counts for
3 papers
On-Policy Model Errors in Reinforcement Learning
Lukas P. Fröhlich, Maksym Lefarov, Melanie N. Zeilinger +1
Model-free reinforcement learning algorithms can compute policy gradients given sampled environment transitions, but require large amounts of data. In contrast, model-based methods…
Contextual Tuning of Model Predictive Control for Autonomous Racing
Lukas P. Fröhlich, Christian Küttel, Elena Arcari +3
Learning-based model predictive control has been widely applied in autonomous racing to improve the closed-loop behaviour of vehicles in a data-driven manner. When environmental co…
Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization
Lukas P. Fröhlich, Edgar D. Klenske, Julia Vinogradska +2
We consider the problem of robust optimization within the well-established Bayesian optimization (BO) framework. While BO is intrinsically robust to noisy evaluations of the object…