Comparison of Different Domain Randomization Methods for Policy Transfer in Reinforcement Learning
Author:
Affiliation:
1. Institute of Automation, Chinese Academy of Sciences,State Key Laboratory of Multimodal Artificial Intelligence Systems,Beijing,China,100190
Funder
National Natural Science Foundation of China (NSFC)
Strategic Priority Research Program of Chinese Academy of Sciences (CAS)
International Partnership Program of the Chinese Academy of Sciences
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10165684/10165785/10166417.pdf?arnumber=10166417
Reference34 articles.
1. Meta Reinforcement Learning for Sim-to-real Domain Adaptation
2. Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
3. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;International Conference on Machine Learning,2018
4. Affordance learning for end-to-end visuomotor robot control;hämäläinen;IEEE/RSJ International Conference on Intelligent Robots and Systems,0
5. Transferring Generalizable Motor Primitives From Simulation to Real World
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