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Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems.
Approximate computation of expectations
Charles Stein · 1986
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Variance reduction techniques for gradient estimates in reinforcement learning
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Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Deterministic policy gradient algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, and Martin Riedmiller · 2014
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Measuring sample quality with stein’s method
Jackson Gorham and Lester Mackey · 2015
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Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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Trust region policy optimization
John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, and Pieter Abbeel · 2015
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Yihao Feng, Dilin Wang, and Qiang Liu · 2017
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Interpolated policy gradient: Merging on-policy and off-policy gradient estimation for deep reinforcement learning
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Qiang Liu and Jason D Lee · 2017
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