English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse
  1. View item / 
  2. Item Summary

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Thesis

Models for Data-Efficient Reinforcement Learning on Real-World Applications

MPS-Authors
/persons/resource/persons192046

Dörr,  Andreas
Max Planck Research Group Intelligent Control Systems, Max Planck Institute for Intelligent Systems, Max Planck Society;
Institut für Parallele und Verteilte Systeme, Universität Stuttgart, Stuttgart;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Dörr, A. (2021). Models for Data-Efficient Reinforcement Learning on Real-World Applications. PhD Thesis, Universität Stuttgart, Stuttgart.


Cite as: https://hdl.handle.net/21.11116/0000-0009-D4CC-2
Abstract
There is no abstract available