cluster #4

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
• 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
• Multi-agent Game Abstraction Via Graph Attention Neural Network (2019)
  Yong Liu, Weixun Wang, Yujing Hu, et al.
  17.02
• Optimization For Reinforcement Learning: From Single Agent To Cooperative Agents (2019)
  Donghwan Lee, Niao He, Parameswaran Kamalaruban, et al.
  14.62
• 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
• Proagent: Building Proactive Cooperative Agents With Large Language Models (2023)
  Ceyao Zhang, Kaijie Yang, Siyi Hu, et al.
  12.74
• 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
• 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
• Stigmergic Independent Reinforcement Learning For Multi-agent Collaboration (2019)
  Xing Xu, Rongpeng Li, Zhifeng Zhao, et al.
  10.85
• Modular Multi-objective Deep Reinforcement Learning With Decision Values (2017)
  Tomasz Tajmajer
  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
• Finite-sample Analysis For Decentralized Batch Multi-agent Reinforcement Learning With Networked Agents (2018)
  Kaiqing Zhang, Zhuoran Yang, Han Liu, et al.
  10.07
• Mathematics Of Multi-agent Learning Systems At The Interface Of Game Theory And Artificial Intelligence (2024)
  Long Wang, Feng Fu, Xingru Chen
  9.92
• Learning-based Physical Layer Communications For Multi-agent Collaboration (2018)
  Arsham Mostaani, Osvaldo Simeone, Symeon Chatzinotas, et al.
  9.59
• Contrastive Identity-aware Learning For Multi-agent Value Decomposition (2022)
  Shunyu Liu, Yihe Zhou, Jie Song, et al.
  9.41
• Real-world Human-robot Collaborative Reinforcement Learning (2020)
  Ali Shafti, Jonas Tjomsland, William Dudley, et al.
  9.41
• QTRAN++: Improved Value Transformation For Cooperative Multi-agent Reinforcement Learning (2020)
  Kyunghwan Son, Sungsoo Ahn, Roben Delos Reyes, et al.
  9.41
• Deep Reinforcement Learning For Multi-agent Interaction (2022)
  Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho, et al.
  9.23
• Intrinsic Fluctuations Of Reinforcement Learning Promote Cooperation (2022)
  Wolfram Barfuss, Janusz Meylahn
  9.23
• Modelling Bounded Rationality In Multi-agent Interactions By Generalized Recursive Reasoning (2019)
  Ying Wen, Yaodong Yang, Rui Luo, et al.
  9.23
• On Centralized Critics In Multi-agent Reinforcement Learning (2024)
  Xueguang Lyu, Andrea Baisero, Yuchen Xiao, et al.
  9.03
• Quantifying The Effects Of Environment And Population Diversity In Multi-agent Reinforcement Learning (2021)
  Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, et al.
  9.03
• Fully Asynchronous Policy Evaluation In Distributed Reinforcement Learning Over Networks (2020)
  Xingyu Sha, Jiaqi Zhang, Keyou You, et al.
  9.03
• Transformer-based Value Function Decomposition For Cooperative Multi-agent Reinforcement Learning In Starcraft (2022)
  Muhammad Junaid Khan, Syed Hammad Ahmed, Gita Sukthankar
  8.82
• Hierarchical Multi-agent Reinforcement Learning For Air Combat Maneuvering (2023)
  Ardian Selmonaj, Oleg Szehr, Giacomo del Rio, et al.
  8.82
• Learning Multi-agent Coordination Through Connectivity-driven Communication (2020)
  Emanuele Pesce, Giovanni Montana
  8.60
• Distributed Value Function Approximation For Collaborative Multi-agent Reinforcement Learning (2020)
  Milos S. Stankovic, Marko Beko, Srdjan S. Stankovic
  8.60
• Smix(\(\lambda\)): Enhancing Centralized Value Functions For Cooperative Multi-agent Reinforcement Learning (2019)
  Xinghu Yao, Chao Wen, Yuhui Wang, et al.
  8.60
• Measuring Collaborative Emergent Behavior In Multi-agent Reinforcement Learning (2018)
  Sean L. Barton, Nicholas R. Waytowich, Erin Zaroukian, et al.
  8.09
• Reinforcement Learning From Hierarchical Critics (2019)
  Zehong Cao, Chin-Teng Lin
  8.09
• Multi-agent Deep Reinforcement Learning With Human Strategies (2018)
  Thanh Nguyen, Ngoc Duy Nguyen, Saeid Nahavandi
  8.09
• Learning Existing Social Conventions Via Observationally Augmented Self-play (2018)
  Adam Lerer, Alexander Peysakhovich
  7.81
• Learning In Cooperative Multiagent Systems Using Cognitive And Machine Models (2023)
  Thuy Ngoc Nguyen, Duy Nhat Phan, Cleotilde Gonzalez
  7.81
• Local Advantage Actor-critic For Robust Multi-agent Deep Reinforcement Learning (2021)
  Yuchen Xiao, Xueguang Lyu, Christopher Amato
  7.81