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Deep reinforcement learning is an effective tool to learn robot control policies from scratch.
1910
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OpenAI, M. Andrychowicz, B. Baker, M. Chociej, R. Józefowicz, B. McGrew, J. W. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L. Weng, and W. Zaremba, “Learning dexterous in-hand manipulation,” Int. J. Robot. Res. , vol. 39, no. 1, 2020. [Online]. Available: https://doi.org/10.1177/0278364919887447
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F. Muratore, C. Eilers, M. Gienger, and J. Peters, “Data-efficient domain randomization with bayesian optimization,” IEEE Robotics Autom. Lett. , vol. 6, no. 2, pp. 911–918, 2021. [Online]. Available: https://doi.org/10.1109/LRA.2021.3052391
2021
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