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Large sequence model (SM) such as GPT series and BERT has displayed outstanding performance and generalization capabilities on vision, language, and recently reinforcement learning tasks.
Markov games as a framework for multi-agent reinforcement learning
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All learning is local: Multi-agent learning in global reward games
Yu-Han Chang, Tracey Ho, and Leslie Kaelbling · 2003
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Natural language processing: an introduction
Prakash M Nadkarni, Lucila Ohno-Machado, and Wendy W Chapman · 2011
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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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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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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel · 2015
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Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, and Igor Mordatch · 2017
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Proximal policy optimization algorithms
John Schulman, F. Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Value-decomposition networks for cooperative multi-agent learning
Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinicius Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z Leibo, Karl Tuyls, et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Counterfactual multi-agent policy gradients
Jakob Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson · 2018
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Qmix: Monotonic value function factorisation for deep multi-agent reinforcement learning
Tabish Rashid, Mikayel Samvelyan, Christian Schroeder, Gregory Farquhar, Jakob Foerster, and Shimon Whiteson · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Probabilistic recursive reasoning for multi-agent reinforcement learning
Ying Wen, Yaodong Yang, Rui Luo, Jun Wang, and Wei Pan · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Google research football: A novel reinforcement learning environment
Karol Kurach, Anton Raichuk, Piotr Stańczyk, Michał Zając, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, et al · 2019
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Maven: Multi-agent variational exploration
Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, and Shimon Whiteson · 2019
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The starcraft multi-agent challenge
Mikayel Samvelyan, Tabish Rashid, Christian Schroeder de Witt, Gregory Farquhar, Nantas Nardelli, Tim GJ Rudner, Chia-Man Hung, Philip HS Torr, Jakob Foerster, and Shimon Whiteson · 2019
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Qtran: Learning to factorize with transformation for cooperative multi-agent reinforcement learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang, David Earl Hostallero, and Yung Yi · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Deep multi-agent reinforcement learning for decentralized continuous cooperative control
Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, and Shimon Whiteson · 2020
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Settling the variance of multi-agent policy gradients
Jakub Grudzien Kuba, Muning Wen, Linghui Meng, Haifeng Zhang, David Mguni, Jun Wang, Yaodong Yang, et al · 2021
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Contrasting centralized and decentralized critics in multi-agent reinforcement learning
Xueguang Lyu, Yuchen Xiao, Brett Daley, and Christopher Amato · 2021
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Linghui Meng, Muning Wen, Yaodong Yang, Chenyang Le, Xiyun Li, Weinan Zhang, Ying Wen, Haifeng Zhang, Jun Wang, and Bo Xu · 2021
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Learning to shape rewards using a game of switching controls
David Mguni, Jianhong Wang, Taher Jafferjee, Nicolas Perez-Nieves, Wenbin Song, Yaodong Yang, Feifei Tong, Hui Chen, Jiangcheng Zhu, Yali Du, et al · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Modelling bounded rationality in multi-agent interactions by generalized recursive reasoning
Ying Wen, Yaodong Yang, and Jun Wang · 2020
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An overview of multi-agent reinforcement learning from game theoretical perspective
Yaodong Yang and Jun Wang · 2020
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Multi-agent determinantal q-learning
Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, and Weinan Zhang · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Decision transformer: Reinforcement learning via sequence modeling
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On the complexity of computing markov perfect equilibrium in general-sum stochastic games
Xiaotie Deng, Yuhao Li, David Henry Mguni, Jun Wang, and Yaodong Yang · 2021
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David Henry Mguni, Taher Jafferjee, Jianhong Wang, Nicolas Perez-Nieves, Oliver Slumbers, Feifei Tong, Yang Li, Jiangcheng Zhu, Yaodong Yang, and Jun Wang · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Going deeper with image transformers
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Crossformer: A versatile vision transformer hinging on cross-scale attention
Wenxiao Wang, Lu Yao, Long Chen, Binbin Lin, Deng Cai, Xiaofei He, and Wei Liu · 2021
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The surprising effectiveness of mappo in cooperative, multi-agent games
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Flamingo: a visual language model for few-shot learning
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Towards human-level bimanual dexterous manipulation with reinforcement learning
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Trust region policy optimisation in multi-agent reinforcement learning
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Heterogeneous-agent mirror learning: A continuum of solutions to cooperative marl
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Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas · 2022
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Maxvit: Multi-axis vision transformer
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