Reinforcement learning today

2022-10-27: Today we share a paper:
- IN-CONTEXT REINFORCEMENT LEARNING WITH ALGORITHM DISTILLATION, by Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih Details
  - download link
  - keywords: algorithm distillation
2022-10-11: Today we share a paper:
- Defining and Characterizing Reward Hacking, by Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, David Krueger Details
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  - keywords: reward hacking
2022-10-07: Today we share a paper:
- How RL Agents Behave When Their Actions Are Modified, by Eric D. Langlois, Tom Everitt Details
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  - keywords: modified action
2022-06-19: Today we share a paper:
- Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations, by Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh Details
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  - keywords: offline
2021-11-06: Today we share a paper:
- Self-Consistent Models and Values, by Gregory Farquhar, Matteo Hessel, Kate Baumli Zita Marinho, Hado van Hasselt, Angelos Filos, David Silver
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  - keywords: model, self-consistent
2021-10-22: Today we share a paper:
- An Empirical Investigation of Representation Learning for Imitation, by Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
  - download link
  - github repo
2021-10-20: Today we share a paper:
- Temporal Abstraction in Reinforcement Learning with the Successor Representation, by Marlos C. Machado, André Barreto, Doina Precup
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2021-10-19: Today we share a paper:
- REPRESENTATION LEARNING VIA INVARIANT CAUSAL MECHANISMS, by Jovana Mitrovic, Brian McWilliams, Jacob Walker, Lars Buesing, Charles Blundell
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  - keywords: causal, representation Learning, self-supervised Learning, contrastive Methods, causality
2021-10-16: Today we share a paper:
- Nash Equilibria in Finite-Horizon Multiagent Concurrent Games, by Senthil Rajasekaran, Moshe Y. Vardi
  - download link
  - keywords: multiagent, Nash, complexity
2021-10-13: Today we share a paper:
- Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research, by Johan S. Obando-Ceron, Pablo Samuel Castro
  - download link
  - github repo
  - keywords: practice, algorithm, rainbow
2021-10-11: Today we share a paper:
- Batch size-invariance for policy optimization, by Jacob Hilton, Karl Cobbe, John Schulman
  - download link
  - keywords: policy, batch-size
2021-10-08: Today we share a paper;
- Recursively Summarizing Books with Human Feedback, by Jeff Wu, Long Ouyang, Daniel M. Ziegler, Nisan Stiennon, Ryan Lowe, Jan Leike, Paul Christiano
  - download link
  - keywords: alignment, summary, gpt-3, language-model
2021-10-06: Today we share a paper:
- Reinforcement Learning with Information-Theoretic Actuation, by Elliot Catt, Marcus Hutter, Joel Veness
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2021-09-28: Today we share a paper:
- Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning, by Yaodong Yang, Jianye Hao, Ben Liao, Kun Shao, Guangyong Chen, Wulong Liu, Hongyao Tang
  - download link
2021-09-24: Today we share a paper:
- A Minimalist Approach to Offline Reinforcement Learning, by Scott Fujimoto, Shixiang Shane Gu
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2021-09-18: Today we share a paper:
- Negotiating team formation using deep reinforcement learning, by Yoram Bachrach, Richard Everett, Edward Hughes, Angeliki Lazaridou, Joel Z. Leibo, Marc Lanctot, Michael Johanson, Wojciech M. Czarnecki, Thore Graepel
  - download link
2021-09-14: Today we share two papers:
- CoBERL: Contrastive BERT for Reinforcement Learning, by Andrea Banino, Tim Scholtes, Adrià Puidomenech Badia, Jovana Mitrovic, Jacob Walker, Charles Blundell
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- Stabilizing Transformers for Reinforcement Learning, by Emilio Parisotto, H. F. Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, M. Botvinick, N. Heess, R. Hadsell
  - download link
2021-07-03: Today we share a paper:
- Causally Correct Partial Models for Reinforcement Learning, by Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing Details
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2020-08-02: Today we share a paper:
- Discovering Reinforcement Learning Algorithms, by Junhyuk Oh Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver Details
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2020-07-06: Today we share a paper:
- An operator view of policy gradient methods, by Dibya Ghosh, Marlos C. Machado, and Nicolas Le Roux Details
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2020-06-24: Today we share a paper:
- The Value-Improvement Path Towards Better Representations for Reinforcement Learning, by Will Dabney, Andre Barreto, Mark Rowland, Robert Dadashi, John Quan, Marc G. Bellemare, and David Silver Details
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2020-06-23: Today we share a paper:
- An Optimistic Perspective on Offline Reinforcement Learning, by Rishabh Agarwal, Dale Schuurmans, and Mohammad Norouzi Details
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2020-05-21: Today we share a paper:
- Deterministic Bellman Residual Minimization, by Ehsan Saleh and Nan Jiang Details
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2020-05-12: Today we share a paper:
- Plan2Vec: Unsupervised Representation Learning by Latent Plans, by Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra Details
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2020-05-11: Today we share a paper:
- The Value of Abstraction, by Mark K. Ho, David Abel, Thomas L. Griffiths, Michael L. Littman Details
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2020-05-05: Today we share a webconf：
- Leverage the Average: An Analysis of Regularization in RL Details
- Speaker: Matthieu Geist
- link
2020-04-27: Today we share a paper:
- Behaviour Suite for Reinforcement Learning, by Ian Osband, Yotam Doron, Matteo Hessel, John Aslanides, Eren Sezener, Andre Saraiva, Katrina McKinney, Tor Lattimore, Csaba Szepesvari, Satinder Singh, Benjamin Van Roy, Richard Sutton, David Silver, Hado Van Hasselt Details
- download link
- code repositary
2020-04-22: Today we share a webconf:
- RLTheory Seminars: a virtual seminar focuses on theoretical reinforcement learning.
- link
2020-04-19: Today we share a paper:
- Artificial and Computational Intelligence in Games: Revolutions in Computational Game AI, by Jialin Liu, Tom Schaul, Pieter Spronck, and Julian Togelius Details
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2020-04-13: Today we share a paper:
- Leverage the Average: an Analysis of Regularization in RL, by Nino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist Details
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2020-04-08: Today we share a podcast of Csaba Szepesvari:
- Csaba Szepesvari of DeepMind shares his views on Bandits, Adversaries, PUCT in AlphaGo / AlphaZero / MuZero, AGI and RL, what is timeless, and more! Details
- link