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This work adopts the very successful distributional perspective on reinforcement learning and adapts it to the continuous control setting.
On the theory of the brownian motion
George E Uhlenbeck and Leonard S Ornstein · 1930
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The variance of discounted markov decision processes
Matthew J. Sobel · 1982
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Likelihood ratio gradient estimation for stochastic systems
Peter W Glynn · 1990
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Policy gradient methods for reinforcement learning with function approximation
Richard S Sutton, David A McAllester, Satinder P Singh, and Yishay Mansour · 2000
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Natural actor-critic
Jan Peters and Stefan Schaal · 2008
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Parametric Return Density Estimation for Reinforcement Learning
Tetsuro Morimura, Hirotaka Hachiya, Masashi Sugiyama, Toshiyuki Tanaka, and Hisashi Kashima · 2010
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Reinforcement learning in feedback control
Roland Hafner and Martin Riedmiller · 2011
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An overview of the developmental process for the modular prosthetic limb
Matthew S. Johannes, John D. Bigelow, James M. Burck, Stuart D. Harshbarger, Matthew V. Kozlowski, and Thomas Van Doren · 2011
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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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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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2015
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MuJoCo HAPTIX: A virtual reality system for hand manipulation
Vikash Kumar and Emanuel Todorov · 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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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
Prioritized experience replay
Tom Schaul, John Quan, Ioannis Antonoglou, and David Silver · 2016
Later among the works it cites.
Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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A distributional perspective on reinforcement learning
Marc G Bellemare, Will Dabney, and Rémi Munos · 2017
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Emergence of locomotion behaviours in rich environments
Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, Ali Eslami, Martin Riedmiller, and David Silver · 2017
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Rainbow: Combining improvements in deep reinforcement learning
Matteo Hessel, Joseph Modayil, Hado Van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar, and David Silver · 2017
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Cited alongside, same era.
Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
Cited alongside, same era.
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 · 2016
Cited alongside, same era.
Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy P Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Later among the works it cites.
Data-efficient deep reinforcement learning for dexterous manipulation
Ivaylo Popov, Nicolas Heess, Timothy Lillicrap, Roland Hafner, Gabriel Barth-Maron, Matej Vecerik, Thomas Lampe, Yuval Tassa, Tom Erez, and Martin Riedmiller · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Distributed prioritized experience replay
Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, and David Silver · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy Lillicrap, and Martin Riedmiller · 2018
Closest in time.