1 citations · 2 across the 6 of their papers we have counts for
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Structure Preserving Approximation of Semiconcave Functions
Karl Kunisch, Donato Vásquez-Varas
This article addresses structure-preserving smooth approximation of semiconcave functions. semiconcave functions are of particular interest because they naturally arise in a variet…
Convergence of machine learning methods for feedback control laws: averaged feedback learning scheme and data driven methods
Karl Kunisch, Donato Vásquez-Varas
This work addresses the synthesis of optimal feedback control laws via machine learning. In particular, the Averaged Feedback Learning Scheme (AFLS) and a data driven method are co…
Smooth approximation of feedback laws for infinite horizon control problems with non-smooth value functions
Karl Kunisch, Donato Vásquez-Varas
In this work the synthesis of approximate optimal and smooth feedback laws for infinite horizon optimal control problems is addressed. In this regards, type error bounds of…
Optimal polynomial feedback laws for finite horizon control problems
Karl Kunisch, Donato Vásquez-Varas
A learning technique for finite horizon optimal control problems and its approximation based on polynomials is analyzed. It allows to circumvent, in part, the curse dimensionality…
Learning Optimal Feedback Operators and their Polynomial Approximation
Karl Kunisch, Donato Vásquez-Varas, Daniel Walter
A learning based method for obtaining feedback laws for nonlinear optimal control problems is proposed. The learning problem is posed such that the open loop value function is its…