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Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement
  Learning with Domain Randomization

Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization

29 July 2022
Y. Kadokawa
Lingwei Zhu
Yoshihisa Tsurumine
Takamitsu Matsubara
ArXivPDFHTML

Papers citing "Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization"

3 / 3 papers shown
Title
Distilled Domain Randomization
Distilled Domain Randomization
J. Brosseit
Benedikt Hahner
Fabio Muratore
Michael Gienger
Jan Peters
16
4
0
06 Dec 2021
Cautious Actor-Critic
Cautious Actor-Critic
Lingwei Zhu
Toshinori Kitamura
Takamitsu Matsubara
AAML
31
1
0
12 Jul 2021
Data-efficient Domain Randomization with Bayesian Optimization
Data-efficient Domain Randomization with Bayesian Optimization
Fabio Muratore
C. Eilers
Michael Gienger
Jan Peters
OOD
72
78
0
05 Mar 2020
1