Multi-Agent

Papers

• Deep Reinforcement Learning For Multi-agent Systems: A Review Of Challenges, Solutions And Applications (2018)
  Thanh Thi Nguyen, Ngoc Duy Nguyen, Saeid Nahavandi
  22.57
• Multi-agent Reinforcement Learning: A Selective Overview Of Theories And Algorithms (2019)
  Kaiqing Zhang, Zhuoran Yang, Tamer Başar
  21.85
• Agentformer: Agent-aware Transformers For Socio-temporal Multi-agent Forecasting (2021)
  Ye Yuan, Xinshuo Weng, Yanglan Ou, et al.
  20.36
• A Survey And Critique Of Multiagent Deep Reinforcement Learning (2018)
  Pablo Hernandez-Leal, Bilal Kartal, Matthew E. Taylor
  20.07
• A Review Of Cooperative Multi-agent Deep Reinforcement Learning (2019)
  Afshin Oroojlooyjadid, Davood Hajinezhad
  19.08
• The Shapley Value In Machine Learning (2022)
  Benedek Rozemberczki, Lauren Watson, Péter Bayer, et al.
  17.35
• Google Research Football: A Novel Reinforcement Learning Environment (2019)
  Karol Kurach, Anton Raichuk, Piotr Stańczyk, et al.
  17.22
• Multi-agent Game Abstraction Via Graph Attention Neural Network (2019)
  Yong Liu, Weixun Wang, Yujing Hu, et al.
  17.02
• Resource Management In Wireless Networks Via Multi-agent Deep Reinforcement Learning (2020)
  Navid Naderializadeh, Jaroslaw Sydir, Meryem Simsek, et al.
  16.43
• Large-scale Traffic Signal Control Using A Novel Multi-agent Reinforcement Learning (2019)
  Xiaoqiang Wang, Liangjun Ke, Zhimin Qiao, et al.
  16.21
• Starcraft Micromanagement With Reinforcement Learning And Curriculum Transfer Learning (2018)
  Kun Shao, Yuanheng Zhu, Dongbin Zhao
  16.19
• Revisiting The Arcade Learning Environment: Evaluation Protocols And Open Problems For General Agents (2017)
  Marlos C. MacHado, Marc G. Bellemare, Erik Talvitie, et al.
  15.67
• A Deep Actor-critic Reinforcement Learning Framework For Dynamic Multichannel Access (2019)
  Chen Zhong, Ziyang Lu, M. Cenk Gursoy, et al.
  15.22
• A Multi-agent Reinforcement Learning Approach For Efficient Client Selection In Federated Learning (2022)
  Sai Qian Zhang, Jieyu Lin, Qi Zhang
  15.00
• Optimization For Reinforcement Learning: From Single Agent To Cooperative Agents (2019)
  Donghwan Lee, Niao He, Parameswaran Kamalaruban, et al.
  14.62
• Evolutionary Reinforcement Learning: A Survey (2023)
  Hui Bai, Ran Cheng, Yaochu Jin
  13.93
• Vizdoom Competitions: Playing Doom From Pixels (2018)
  Marek Wydmuch, Michał Kempka, Wojciech Jaśkowski
  13.79
• Shapley Q-value: A Local Reward Approach To Solve Global Reward Games (2019)
  Jianhong Wang, Yuan Zhang, Tae-Kyun Kim, et al.
  13.65
• Resilient Autonomous Control Of Distributed Multi-agent Systems In Contested Environments (2017)
  Rohollah Moghadam, Hamidreza Modares
  13.11
• Communication-efficient Policy Gradient Methods For Distributed Reinforcement Learning (2018)
  Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis, et al.
  13.05
• Scalable Photonic Reinforcement Learning By Time-division Multiplexing Of Laser Chaos (2018)
  Makoto Naruse, Takatomo Mihana, Hirokazu Hori, et al.
  13.05
• Proagent: Building Proactive Cooperative Agents With Large Language Models (2023)
  Ceyao Zhang, Kaijie Yang, Siyi Hu, et al.
  12.74
• Multi-step Reinforcement Learning: A Unifying Algorithm (2017)
  Kristopher de Asis, J. Fernando Hernandez-Garcia, G. Zacharias Holland, et al.
  12.68
• Multi-agent Trust Region Policy Optimization (2020)
  Hepeng Li, Haibo He
  12.61
• Deep Multi-agent Reinforcement Learning With Discrete-continuous Hybrid Action Spaces (2019)
  Haotian Fu, Hongyao Tang, Jianye Hao, et al.
  12.47
• Shapley Counterfactual Credits For Multi-agent Reinforcement Learning (2021)
  Jiahui Li, Kun Kuang, Baoxiang Wang, et al.
  12.40
• Improving Coordination In Small-scale Multi-agent Deep Reinforcement Learning Through Memory-driven Communication (2019)
  Emanuele Pesce, Giovanni Montana
  12.25
• On Passivity, Reinforcement Learning And Higher-order Learning In Multi-agent Finite Games (2018)
  Bolin Gao, Lacra Pavel
  12.02
• Sa-matd3:self-attention-based Multi-agent Continuous Control Method In Cooperative Environments (2021)
  Kai Liu, Yuyang Zhao, Gang Wang, et al.
  11.76
• Distributed Off-policy Actor-critic Reinforcement Learning With Policy Consensus (2019)
  Yan Zhang, Michael M. Zavlanos
  11.67
• Factorized Q-learning For Large-scale Multi-agent Systems (2018)
  Ming Zhou, Yong Chen, Ying Wen, et al.
  11.58
• A Multi-agent Off-policy Actor-critic Algorithm For Distributed Reinforcement Learning (2019)
  Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, et al.
  11.39
• Distributed Deep Reinforcement Learning: A Survey And A Multi-player Multi-agent Learning Toolbox (2022)
  Qiyue Yin, Tongtong Yu, Shengqi Shen, et al.
  11.39
• Winning Isn't Everything: Enhancing Game Development With Intelligent Agents (2019)
  Yunqi Zhao, Igor Borovikov, Fernando de Mesentier Silva, et al.
  11.29
• Robust Model-free Reinforcement Learning With Multi-objective Bayesian Optimization (2019)
  Matteo Turchetta, Andreas Krause, Sebastian Trimpe
  11.08
• Multi-agent Inverse Reinforcement Learning For Certain General-sum Stochastic Games (2018)
  Xiaomin Lin, Stephen C. Adams, Peter A. Beling
  10.97
• Elastic Step DQN: A Novel Multi-step Algorithm To Alleviate Overestimation In Deep Qnetworks (2022)
  Adrian Ly, Richard Dazeley, Peter Vamplew, et al.
  10.85
• Stigmergic Independent Reinforcement Learning For Multi-agent Collaboration (2019)
  Xing Xu, Rongpeng Li, Zhifeng Zhao, et al.
  10.85
• Sok: Adversarial Machine Learning Attacks And Defences In Multi-agent Reinforcement Learning (2023)
  Maxwell Standen, Junae Kim, Claudia Szabo
  10.74
• Modular Multi-objective Deep Reinforcement Learning With Decision Values (2017)
  Tomasz Tajmajer
  10.74
• Adaptive Incentive For Cross-silo Federated Learning: A Multi-agent Reinforcement Learning Approach (2023)
  Shijing Yuan, Hongze Liu, Hongtao Lv, et al.
  10.74
• Policy Distillation And Value Matching In Multiagent Reinforcement Learning (2019)
  Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, et al.
  10.48
• Scalable Reinforcement Learning For Multi-agent Networked Systems (2019)
  Guannan Qu, Adam Wierman, Na Li
  10.35
• Cooperative Multi-agent Reinforcement Learning With Partial Observations (2020)
  Yan Zhang, Michael M. Zavlanos
  10.35
• Multi-agent Fully Decentralized Value Function Learning With Linear Convergence Rates (2018)
  Lucas Cassano, Kun Yuan, Ali H. Sayed
  10.21
• Scalable Reinforcement Learning Policies For Multi-agent Control (2020)
  Christopher D. Hsu, Heejin Jeong, George J. Pappas, et al.
  10.21
• Residual Q-networks For Value Function Factorizing In Multi-agent Reinforcement Learning (2022)
  Rafael Pina, Varuna de Silva, Joosep Hook, et al.
  10.21
• Reinforcement Learning In Non-stationary Discrete-time Linear-quadratic Mean-field Games (2020)
  Muhammad Aneeq Uz Zaman, Kaiqing Zhang, Erik Miehling, et al.
  10.07
• Finite-sample Analysis For Decentralized Batch Multi-agent Reinforcement Learning With Networked Agents (2018)
  Kaiqing Zhang, Zhuoran Yang, Han Liu, et al.
  10.07
• Multi-objective Reinforcement Learning Based On Decomposition: A Taxonomy And Framework (2023)
  Florian Felten, El-Ghazali Talbi, Grégoire Danoy
  9.92