Title data
Sperl, Mario ; Saluzzi, Luca ; Grüne, Lars ; Kalise, Dante:
Separable approximations of optimal value functions under a decaying sensitivity assumption.
In:
62nd IEEE Conference on Decision and Control (CDC) 2023. -
Singapore, Singapore
,
2023
. - pp. 259-264
DOI: https://doi.org/10.1109/CDC49753.2023.10383497
This is the latest version of this item.
Project information
| Project title: |
Project's official title Project's id Nichtlineare optimale Feedback-Regelung mit tiefen neuronalen Netzen ohne den Fluch der Dimension: Räumlich abnehmende Sensitivität und nichtglatte Probleme 463912816 |
|---|---|
| Project financing: |
Deutsche Forschungsgemeinschaft |
Abstract in another language
An efficient 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
Available Versions of this Item
-
Separable approximations of optimal value functions under a decaying sensitivity assumption. (deposited 17 Apr 2023 07:43)
- Separable approximations of optimal value functions under a decaying sensitivity assumption. (deposited 02 Feb 2024 11:10) [Currently Displayed]

at Google Scholar