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Off-policy learning algorithms have been known to be sensitive to the choice of hyper-parameters.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
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Ronald J Williams · 1992
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 1998
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Nikolaus Hansen, Sibylle D Müller, and Petros Koumoutsakos · 2003
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A tutorial on the cross-entropy method
Pieter-Tjerk De Boer, Dirk P Kroese, Shie Mannor, and Reuven Y Rubinstein · 2005
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Thomas Degris, Martha White, and Richard S Sutton · 2012
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The arcade learning environment: An evaluation platform for general agents
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Diederik P Kingma and Max Welling · 2013
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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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Natural evolution strategies
Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, and Jürgen Schmidhuber · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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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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Dueling network architectures for deep reinforcement learning
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado Van Hasselt, Marc Lanctot, and Nando De Freitas · 2015
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Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
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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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Adaptive lambda least-squares temporal difference learning
Timothy A Mann, Hugo Penedones, Shie Mannor, and Todd Hester · 2016
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Volodymyr Mnih, Adria Puigdomenech Badia, Mehdi Mirza, Alex Graves, Timothy Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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David Ha and Jürgen Schmidhuber · 2018
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Addressing function approximation error in actor-critic methods
Scott Fujimoto, Herke Van Hoof, and David Meger · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Structured evolution with compact architectures for scalable policy optimization
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Max Jaderberg, Valentin Dalibard, Simon Osindero, Wojciech M Czarnecki, Jeff Donahue, Ali Razavi, Oriol Vinyals, Tim Green, Iain Dunning, Karen Simonyan, et al · 2017
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Evolution strategies as a scalable alternative to reinforcement learning
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, and Ilya Sutskever · 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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Roboschool, 2017
Oleg Klimov and John Schulman · 2017
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Deep reinforcement learning and the deadly triad
Hado Van Hasselt, Yotam Doron, Florian Strub, Matteo Hessel, Nicolas Sonnerat, and Joseph Modayil · 2018
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Recurrent experience replay in distributed reinforcement learning
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Off-policy deep reinforcement learning without exploration
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Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E Turner, and Adrian Weller · 2018
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Simple random search provides a competitive approach to reinforcement learning
Horia Mania, Aurelia Guy, and Benjamin Recht · 2018
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Evolution-guided policy gradient in reinforcement learning
Shauharda Khadka and Kagan Tumer · 2018
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Cem-rl: Combining evolutionary and gradient-based methods for policy search
Aloïs Pourchot and Olivier Sigaud · 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, et al · 2018
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Maximum a posteriori policy optimisation
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Remi Munos, Nicolas Heess, and Martin Riedmiller · 2018
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Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
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Openai spinning up
Joshua Achiam · 2018
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Adaptive trade-offs in off-policy learning
Mark Rowland, Will Dabney, and Rémi Munos · 2019
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Fast efficient hyperparameter tuning for policy gradients
Supratik Paul, Vitaly Kurin, and Shimon Whiteson · 2019
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Self-tuning deep reinforcement learning
Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, and Satinder Singh · 2020
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