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Separable approximations of optimal value functions under a decaying sensitivity assumption

Title data

Sperl, Mario ; Saluzzi, Luca ; Grüne, Lars ; Kalise, Dante:
Separable approximations of optimal value functions under a decaying sensitivity assumption.
Bayreuth , 2023
DOI: https://doi.org/10.48550/arXiv.2304.06379

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Project information

Project title:
Project's official title
Project's id
Curse-of-dimensionality-free nonlinear optimal feedback control with deep neural networks. A compositionality-based approach via Hamilton-Jacobi-Bellman PDEs
463912816

Project financing: Deutsche Forschungsgemeinschaft

Abstract in another language

A new approach for the construction of separable approximations of optimal value functions from interconnected optimal control problems is presented. The approach is based on assuming decaying sensitivities between subsystems, enabling a curse-of-dimensionality free approximation, for instance by deep neural networks.

Further data

Item Type: Preprint, postprint
Refereed: Yes
Keywords: Optimal control; computational methods
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Applied Mathematics
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Advanced Fields > Nonlinear Dynamics
Research Institutions
Research Institutions > Central research institutes
Research Institutions > Central research institutes > Bayreuth Research Center for Modeling and Simulation - MODUS
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 17 Apr 2023 07:43
Last Modified: 17 Apr 2023 07:43
URI: https://eref.uni-bayreuth.de/id/eprint/75956

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