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In this paper, a new adaptive multi-batch experience replay scheme is proposed for proximal policy optimization (PPO) for continuous action control.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
Earlier work this paper cites.
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Earlier work this paper cites.
On-line Q-learning using connectionist systems
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Earlier work this paper cites.
Reinforcement learning: An introduction
R. S. Sutton and A. G. Barto · 1998
Earlier work this paper cites.
Policy gradient methods for reinforcement learning with function approximation
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Ziyu Wang, Victor Bapst, Nicolas Heess, Volodymyr Mnih, Remi Munos, Koray Kavukcuoglu, and Nando de Freitas · 2016
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