-
Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimization
Myeung Suk Oh, Zhiyao Zhang, Hairi, Alvaro Velasquez and Jia Liu
-
Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach
Hairi, Jiao Yang, Tianchen Zhou, Haibo Yang, Chaosheng Dong, Fan Yang, Michinari Momma, Yan Gao, Jia Liu
-
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang*, Myeung Suk Oh*, Hairi, Ziyue Luo, Alvaro Velasquez and Jia Liu
-
On the Hardness of Decentralized Multi-agent Policy Evaluation under Byzantine Attacks
Hairi*, Minghong Fang*, Zifan Zhang, Alvaro Velasquez and Jia Liu
-
Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
Hairi*, Tianchen Zhou*, Haibo Yang, Jia Liu, Tian Tong, Fan Yang, Michinari Momma, and Yan Gao
-
Byzantine-Robust Decentralized Federated Learning
Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu and Neil Gong
-
Sample and Communication Efficient Fully Decentralized MARL Policy Evaluation via a New Approach: Local TD Update
Hairi, Zifan Zhang and Jia Liu
-
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
Hairi, Jia Liu and Songtao Lu
-
Beyond Scaling: Calculable Error Bounds of the Power-of-Two Choices Mean-Field Model in Heavy-Traffic
Hairi, Xin Liu and Lei Ying
-
NetDyna: Mining Networked Coevolving Time Series with Missing Values
Hairi, Hanghang Tong and Lei Ying