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Policy distillation, which transfers a teacher policy to a student policy has achieved great success in challenging tasks of deep reinforcement learning.
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Guided cost learning: Deep inverse optimal control via policy optimization
Chelsea Finn, Sergey Levine, and Pieter Abbeel · 2016
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Cooperative inverse reinforcement learning
Dylan Hadfield-Menell, Stuart J Russell, Pieter Abbeel, and Anca Dragan · 2016
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Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2016
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Policy distillation
Andrei A Rusu, Sergio Gomez Colmenarejo, Caglar Gulcehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, and Raia Hadsell · 2016
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Simultaneously learning and advising in multiagent reinforcement learning
Felipe Leno Da Silva, Ruben Glatt, and Anna Helena Reali Costa · 2017
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Todd Hester, Matej Vecerik, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, et al · 2018
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Self-imitation learning
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Learning to explore via meta-policy gradient
Tianbing Xu, Qiang Liu, Liang Zhao, and Jian Peng · 2018
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Meta-gradient reinforcement learning
Zhongwen Xu, Hado P van Hasselt, and David Silver · 2018
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Distral: Robust multitask reinforcement learning
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Wojciech Marian Czarnecki, Razvan Pascanu, Simon Osindero, Siddhant M Jayakumar, Grzegorz Swirszcz, and Max Jaderberg · 2019
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Learning to teach in cooperative multiagent reinforcement learning
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Rlcard: A toolkit for reinforcement learning in card games
Daochen Zha, Kwei-Herng Lai, Yuanpu Cao, Songyi Huang, Ruzhe Wei, Junyu Guo, and Xia Hu · 2019
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Experience replay optimization
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, and Xia Hu · 2019
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