5 citations · 5 across the 7 of their papers we have counts for
3 papers · 1 filter
A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects
David Stenger, Paul Brunzema, Johanna Menn +3
In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. This article offers a comprehen…
Local Preferential Bayesian Optimization
Johanna Menn, Miriam Kober, Paul Brunzema +2
Bayesian optimization (BO) is a popular and effective approach for tuning expensive, noisy experiments, but requires the formulation of an explicit objective function. Preferential…
Preferential Bayesian Optimization with Crash Feedback
Johanna Menn, David Stenger, Sebastian Trimpe
Bayesian optimization is a popular black-box optimization method for parameter learning in control and robotics. It typically requires an objective function that reflects the user'…