Bayesian Optimization
Reinforcement learning
learning from experience
Model predictive control (MPC)
Procedure: solve optimization problem in
every time-step and apply first piece of
optimal control input
+ Good results for nonlinear systems
+ Extensions for robust & stochastic control
+ Theoretical guarantees
- Computationally expensive!!!
-> approximate controller with ML
initialize, choose points of highest improvement
Used for:
hyperparameter optimization of ML methods
Zuletzt geändertvor 4 Monaten
