Optimal feedback law recovery by gradient-augmented sparse polynomial regression
(2021)
Journal Article
Azmi, B., Kalise, D., & Kunisch, K. (2021). Optimal feedback law recovery by gradient-augmented sparse polynomial regression. Journal of Machine Learning Research, 22, 1-32
A sparse regression approach for the computation of high-dimensional optimal feedback laws arising in deterministic nonlinear control is proposed. The approach exploits the control-theoretical link between Hamilton-Jacobi-Bellman PDEs characterizing... Read More about Optimal feedback law recovery by gradient-augmented sparse polynomial regression.