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Policy gradient methods are appealing in deep reinforcement learning but suffer from high variance of gradient estimate.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Reinforcement learning: An introduction
Richard S. Sutton and Andrew G. Barto · 1998
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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 · 1999
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The information bottleneck method
Naftali Tishby, Fernando C. N. Pereira, and William Bialek · 2000
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A natural policy gradient
Sham M. Kakade · 2001
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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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 A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis · 2015
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Trust region policy optimization
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
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Asynchronous methods for deep reinforcement learning
Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, and Koray Kavukcuoglu · 2016
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Variance reduction for policy gradient with action-dependent factorized baselines
Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, and Pieter Abbeel · 2018
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Variance reduction for reinforcement learning in input-driven environments
Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf, and Mohammad Alizadeh · 2019
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CLUB: A contrastive log-ratio upper bound of mutual information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, and Lawrence Carin · 2020
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Unsupervised multi-target domain adaptation: An information theoretic approach
Behnam Gholami, Pritish Sahu, Ognjen Rudovic, Konstantinos Bousmalis, and Vladimir Pavlovic · 2020
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