cluster #1

Papers

• Multi-agent Reinforcement Learning: A Selective Overview Of Theories And Algorithms (2019)
  Kaiqing Zhang, Zhuoran Yang, Tamer Başar
  21.85
• 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
• 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
• Deterministic Limit Of Temporal Difference Reinforcement Learning For Stochastic Games (2018)
  Wolfram Barfuss, Jonathan F. Donges, Jürgen Kurths
  12.93
• On Passivity, Reinforcement Learning And Higher-order Learning In Multi-agent Finite Games (2018)
  Bolin Gao, Lacra Pavel
  12.02
• Actor-critic Network For O-RAN Resource Allocation: Xapp Design, Deployment, And Analysis (2022)
  Mohammadreza Kouchaki, Vuk Marojevic
  11.76
• Federated Ensemble Model-based Reinforcement Learning In Edge Computing (2021)
  Jin Wang, Jia Hu, Jed Mills, et al.
  11.58
• Riemannian Game Dynamics (2016)
  Panayotis Mertikopoulos, William H. Sandholm
  11.29
• Safe And Accelerated Deep Reinforcement Learning-based O-RAN Slicing: A Hybrid Transfer Learning Approach (2023)
  Ahmad M. Nagib, Hatem Abou-Zeid, Hossam S. Hassanein
  11.29
• Incorporating Behavioral Constraints In Online AI Systems (2018)
  Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei, et al.
  11.19
• Adaptive Incentive For Cross-silo Federated Learning: A Multi-agent Reinforcement Learning Approach (2023)
  Shijing Yuan, Hongze Liu, Hongtao Lv, et al.
  10.74
• Learning Generalized Wireless MAC Communication Protocols Via Abstraction (2022)
  Luciano Miuccio, Salvatore Riolo, Sumudu Samarakoon, et al.
  10.61
• 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
• Multi-objective Reinforcement Learning Based On Decomposition: A Taxonomy And Framework (2023)
  Florian Felten, El-Ghazali Talbi, Grégoire Danoy
  9.92
• MACS: Deep Reinforcement Learning Based SDN Controller Synchronization Policy Design (2019)
  Ziyao Zhang, Liang Ma, Konstantinos Poularakis, et al.
  9.92
• Partially Observable Mean Field Multi-agent Reinforcement Learning Based On Graph-attention (2023)
  Min Yang, Guanjun Liu, Ziyuan Zhou
  9.76
• Offline Reinforcement Learning For Wireless Network Optimization With Mixture Datasets (2023)
  Kun Yang, Cong Shen, Jing Yang, et al.
  9.59
• Decentralized Federated Reinforcement Learning For User-centric Dynamic TFDD Control (2022)
  Ziyan Yin, Zhe Wang, Jun Li, et al.
  9.41
• Channel Estimation Via Successive Denoising In MIMO OFDM Systems: A Reinforcement Learning Approach (2021)
  Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim, et al.
  9.23
• Digital Twin-assisted Efficient Reinforcement Learning For Edge Task Scheduling (2022)
  Xiucheng Wang, Longfei Ma, Haocheng Li, et al.
  9.23
• A Generalized Minimax Q-learning Algorithm For Two-player Zero-sum Stochastic Games (2019)
  Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi, Shalabh Bhatnagar
  9.03
• Multi-agent Online Learning In Time-varying Games (2018)
  Benoit Duvocelle, Panayotis Mertikopoulos, Mathias Staudigl, et al.
  8.82
• Acceleration For Deep Reinforcement Learning Using Parallel And Distributed Computing: A Survey (2024)
  Zhihong Liu, Xin Xu, Peng Qiao, et al.
  8.82
• Symmetric Equilibrium Of Multi-agent Reinforcement Learning In Repeated Prisoner's Dilemma (2021)
  Yuki Usui, Masahiko Ueda
  8.60
• Quantifying The Impact Of Non-stationarity In Reinforcement Learning-based Traffic Signal Control (2020)
  Lucas N. Alegre, Ana L. C. Bazzan, Bruno C. da Silva
  8.35
• A Safe Deep Reinforcement Learning Approach For Energy Efficient Federated Learning In Wireless Communication Networks (2023)
  Nikolaos Koursioumpas, Lina Magoula, Nikolaos Petropouleas, et al.
  8.09
• Generalization In Mean Field Games By Learning Master Policies (2021)
  Sarah Perrin, Mathieu Laurière, Julien Pérolat, et al.
  7.81
• Network Slicing Via Transfer Learning Aided Distributed Deep Reinforcement Learning (2023)
  Tianlun Hu, Qi Liao, Qiang Liu, et al.
  7.50
• Multi-agent Deep Reinforcement Learning (MADRL) Meets Multi-user MIMO Systems (2021)
  Heunchul Lee, Jaeseong Jeong
  7.50
• Human-ai Learning Performance In Multi-armed Bandits (2018)
  Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, et al.
  7.50
• Multi-agent Reinforcement Learning For Power Control In Wireless Networks Via Adaptive Graphs (2023)
  Lorenzo Mario Amorosa, Marco Skocaj, Roberto Verdone, et al.
  7.16
• Score Vs. Winrate In Score-based Games: Which Reward For Reinforcement Learning? (2022)
  Luca Pasqualini, Gianluca Amato, Marco Fantozzi, et al.
  7.16
• Opponent Learning Awareness And Modelling In Multi-objective Normal Form Games (2020)
  Roxana Rădulescu, Timothy Verstraeten, Yijie Zhang, et al.
  7.16
• A Reinforcement Learning Approach For The Multichannel Rendezvous Problem (2019)
  Jen-Hung Wang, Ping-En Lu, Cheng-Shang Chang, et al.
  7.16
• Leveraging Digital Cousins For Ensemble Q-learning In Large-scale Wireless Networks (2024)
  Talha Bozkus, Urbashi Mitra
  6.77
• Distributed TD(0) With Almost No Communication (2021)
  Rui Liu, Alex Olshevsky
  6.77
• Independent Learning In Stochastic Games (2021)
  Asuman Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang
  6.77
• Reinforcement Learning In Nonzero-sum Linear Quadratic Deep Structured Games: Global Convergence Of Policy Optimization (2020)
  Masoud Roudneshin, Jalal Arabneydi, Amir G. Aghdam
  6.77
• Fictitious Play In Markov Games With Single Controller (2022)
  Muhammed O. Sayin, Kaiqing Zhang, Asuman Ozdaglar
  6.77
• Joint Optimization Of Multi-objective Reinforcement Learning With Policy Gradient Based Algorithm (2021)
  Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal
  6.34
• Simple Uncoupled No-regret Learning Dynamics For Extensive-form Correlated Equilibrium (2021)
  Gabriele Farina, Andrea Celli, Alberto Marchesi, et al.
  6.34
• Implications Of Regret On Stability Of Linear Dynamical Systems (2022)
  Aren Karapetyan, Anastasios Tsiamis, Efe C. Balta, et al.
  6.34
• Reinforcement Learning In Linear Quadratic Deep Structured Teams: Global Convergence Of Policy Gradient Methods (2020)
  Vida Fathi, Jalal Arabneydi, Amir G. Aghdam
  5.84
• Dynamic Channel Access Via Meta-reinforcement Learning (2021)
  Ziyang Lu, M. Cenk Gursoy
  5.84
• On The Variational Interpretation Of Mirror Play In Monotone Games (2024)
  Yunian Pan, Tao Li, Quanyan Zhu
  5.84
• An Empirical Study On The Practical Impact Of Prior Beliefs Over Policy Types (2019)
  Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
  5.24
• Sample-efficient Multi-objective Learning Via Generalized Policy Improvement Prioritization (2023)
  Lucas N. Alegre, Ana L. C. Bazzan, Diederik M. Roijers, et al.
  5.24
• Online Learning For Cooperative Multi-player Multi-armed Bandits (2021)
  William Chang, Mehdi Jafarnia-Jahromi, Rahul Jain
  5.24