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Recent advances in multi-agent reinforcement learning have been largely limited in training one model from scratch for every new task.
Multi-agent reinforcement learning: Independent vs. cooperative agents
Ming Tan · 1993
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Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Transfer learning for reinforcement learning domains: A survey
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Generalized model learning for reinforcement learning on a humanoid robot
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Transfer learning in multi-agent reinforcement learning domains
Georgios Boutsioukis, Ioannis Partalas, and Ioannis Vlahavas · 2011
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Reinforcement learning transfer via sparse coding
Haitham B Ammar, Karl Tuyls, Matthew E Taylor, Kurt Driessens, and Gerhard Weiss · 2012
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Empirical evaluation of gated recurrent neural networks on sequence modeling
Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio · 2014
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Deep recurrent q-learning for partially observable mdps
Matthew Hausknecht and Peter Stone · 2015
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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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A concise introduction to decentralized POMDPs , volume 1
Frans A Oliehoek, Christopher Amato, et al · 2016
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A decomposable attention model for natural language inference
Ankur P Parikh, Oscar Täckström, Dipanjan Das, and Jakob Uszkoreit · 2016
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Counterfactual multi-agent policy gradients
Jakob Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson · 2017
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Learning invariant feature spaces to transfer skills with reinforcement learning
Abhishek Gupta, Coline Devin, YuXuan Liu, Pieter Abbeel, and Sergey Levine · 2017
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Multi-agent actor-critic for mixed cooperative-competitive environments
Ryan Lowe, Yi I Wu, Aviv Tamar, Jean Harb, OpenAI Pieter Abbeel, and Igor Mordatch · 2017
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Peng Peng, Ying Wen, Yaodong Yang, Quan Yuan, Zhenkun Tang, Haitao Long, and Jun Wang · 2017
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Value-decomposition networks for cooperative multi-agent learning
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, and Jun Wang · 2018
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A survey on transfer learning for multiagent reinforcement learning systems
Felipe Leno Da Silva and Anna Helena Reali Costa · 2019
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Liir: Learning individual intrinsic reward in multi-agent reinforcement learning
Yali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, and Dacheng Tao · 2019
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Learning to factorize with transformation for cooperative multi-agent reinforcement learning
Wan Ju Kang David Earl Hostallero, Kyunghwan Son, Daewoo Kim, and Yung Yi Qtran · 2019
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Attention is all you need
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Kun Shao, Yuanheng Zhu, and Dongbin Zhao · 2018
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Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, and Shimon Whiteson · 2019
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Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al · 2019
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Yaodong Yang, Ying Wen, Lihuan Chen, Jun Wang, Kun Shao, David Mguni, and Weinan Zhang · 2020
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Learning implicit credit assignment for multi-agent actor-critic
Meng Zhou, Ziyu Liu, Pengwei Sui, Yixuan Li, and Yuk Ying Chung · 2020
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Vision-language navigation with self-supervised auxiliary reasoning tasks
Fengda Zhu, Yi Zhu, Xiaojun Chang, and Xiaodan Liang · 2020
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