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We study deep reinforcement learning (RL) algorithms with delayed rewards.
Temporal credit assignment in reinforcement learning
Richard Stuart Sutton · 1984
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Policy invariance under reward transformations: Theory and application to reward shaping
A. Ng, D. Harada, and S. Russell · 1999
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Off-policy actor-critic
Thomas Degris, Martha White, and Richard S Sutton · 2012
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 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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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2014
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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
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Deep learning , volume 1
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio · 2016
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Benchmarking deep reinforcement learning for continuous control
Yan Duan, Xi Chen, Rein Houthooft, John Schulman, and Pieter Abbeal · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
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Openai gym, 2016
Brockman Greg, Cheung Vicki, Pettersson Ludwig, Schneider Jonas, Schulman John, Tang Jie, and Zaremba Wojciech · 2016
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Aj Antonoglou, Ioannis abd Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis · 2017
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A benchmark environment motivated by industrial control problems
D. Hein, S. Depeweg, M. Tokic, S. Udluft, A. Hentschel, T. A. Runkler, and V. Sterzing · 2017
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Molecular de-novo design through deep reinforcement learning
Marcus Olivecrona, Thomas Blaschke, Ola Engkvist, and Hongming Chen · 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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan Gomez, N, Lukasz Kaiser, and Illia Polosukhin · 2017
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Generative adversarial self-imitation learning
Yijie Guo, Junhyuk Oh, Satinder Singh, and Honglak Lee · 2018
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Decentralized network level adaptive signal control by multi-agent deep reinforcement learning
Yaobang Gong, Mohamed Abdel-Aty, Qing Cai, and Md Sharikur Rahman · 2019
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Rudder: Return decomposition for delayed rewards
Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, and Sepp Hochreiter · 2019
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Learning self-imitating diverse policies
Tanmay Gangwani, Qiang Liu, and Jian Peng · 2019
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Sequence modeling of temporal credit assignment for episodic reinforcement learning
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Openai baselines
Prafulla Dhariwal, Christopher Hesse, Oleg Klimov, Alex Nichol, Matthias Plappert, Alec Radford, John Schulman, Szymon Sidor, Yuhuai Wu, and Peter Zhokhov · 2017
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Efficient large-scale fleet management via multi-agent deep reinforcement learning
Kaixiang Lin, Renyu Zhao, Zhe Xu, and Jiayu Zhou · 2018
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Large-scale order dispatch in on-demand ride-hailing platforms: A learning and planning approach
Zhe Xu, Zhixin Li, Qingwen Guan, Dingshui Zhang, and Jieping Ye · 2018
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On learning intrinsic rewards for policy gradient methods
Zeyu Zheng, Junhyuk Oh, and Satinder Singh · 2018
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Self-imitation learning
Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
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Addressing function approximation error in actor-critic methods
Scott Fujimoto, Herke Hoof, and David Meger · 2018
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Soft actor-critic algorithms and applications
Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, et al
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Yang Liu, Yunan Luo, Yuanyi Zhong, Xi Chen, Qiang Liu, and Jian Peng · 2019
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Learning guidance rewards with trajectory-space smoothing
Tanmay Gangwani, Yuan Zhou, and Jian Peng · 2020
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Reward propagation using graph convolutional networks martin
Martin Klissarov and Doina Precup · 2020
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeal, and Sergey Levine · 2020
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Offline reinforcement learning: Tutorial, review, and perspectives on open problems
Sergey Levine, Aviral Kumar, George Tucker, and Justin Fu · 2020
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