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OffCon$^3$: What is state of the art anyway?
v1v2 (latest)

OffCon3^33: What is state of the art anyway?

27 January 2021
Philip J. Ball
Stephen J. Roberts
    OffRL
ArXiv (abs)PDFHTML

Papers citing "OffCon$^3$: What is state of the art anyway?"

5 / 5 papers shown
Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification
Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification
Rudolf Reiter
Jasper Hoffmann
D. Reinhardt
Florian Messerer
Katrin Baumgärtner
Shamburaj Sawant
Joschka Boedecker
Moritz Diehl
S. Gros
419
25
0
04 Feb 2025
AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model
  Predictive Control
AC4MPC: Actor-Critic Reinforcement Learning for Nonlinear Model Predictive Control
Rudolf Reiter
Andrea Ghezzi
Katrin Baumgärtner
Jasper Hoffmann
Robert D. McAllister
Moritz Diehl
233
14
0
06 Jun 2024
Efficient Online Reinforcement Learning with Offline Data
Efficient Online Reinforcement Learning with Offline DataInternational Conference on Machine Learning (ICML), 2023
Philip J. Ball
Laura M. Smith
Ilya Kostrikov
Sergey Levine
OffRLOnRL
700
310
0
06 Feb 2023
Is Model Ensemble Necessary? Model-based RL via a Single Model with
  Lipschitz Regularized Value Function
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value FunctionInternational Conference on Learning Representations (ICLR), 2023
Ruijie Zheng
Xiyao Wang
Huazhe Xu
Furong Huang
316
19
0
02 Feb 2023
Tactical Optimism and Pessimism for Deep Reinforcement Learning
Tactical Optimism and Pessimism for Deep Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021
Theodore H. Moskovitz
Jack Parker-Holder
Aldo Pacchiano
Michael Arbel
Sai Li
509
71
0
07 Feb 2021
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