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CASIA OpenIR
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FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game 期刊论文
IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, 页码: 1-13
作者:  Guangzheng Hu;  Yuanheng Zhu;  Haoran Li;  Dongbin Zhao
Adobe PDF(2144Kb)  |  收藏  |  浏览/下载：51/11  |  提交时间：2024/06/05
Games  Q-learning  Task analysis  Optimization  Convergence  Training  Nash equilibrium  Multi-agent reinforcement learning  minimax-Q learning  two-team zero-sum Markov games  
NVIF: Neighboring Variational Information Flow for Cooperative Large-Scale Multiagent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13
作者:  Chai, Jiajun;  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2469Kb)  |  收藏  |  浏览/下载：65/5  |  提交时间：2023/11/16
Large-scale multiagent  neighboring communication  reinforcement learning (RL)  variational information flow  
Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 3, 页码: 1228-1241
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：258/15  |  提交时间：2022/06/10
Games  Nash equilibrium  Mathematical model  Markov processes  Convergence  Dynamic programming  Training  Deep reinforcement learning (DRL)  generalized policy iteration (GPI)  Markov game (MG)  Nash equilibrium  Q network  zero sum  
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
Adobe PDF(4187Kb)  |  收藏  |  浏览/下载：274/13  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)  
Data-driven adaptive dynamic programming for continuous-time fully cooperative games with partially constrained inputs 期刊论文
NEUROCOMPUTING, 2017, 卷号: 238, 期号: *, 页码: 377-386
作者:  Zhang, Qichao;  Zhao, Dongbin;  Zhu, Yuanheng
浏览  |  Adobe PDF(1508Kb)  |  收藏  |  浏览/下载：673/285  |  提交时间：2017/05/04
Adaptive Dynamic Programming  Optimal Control  Neural Network  Fully Cooperative Games  Data-driven  Constrained Input  
Convergence Proof of Approximate Policy Iteration for Undiscounted Optimal Control of Discrete-Time Systems 期刊论文
COGNITIVE COMPUTATION, 2015, 卷号: 7, 期号: 6, 页码: 763-771
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo;  Ji, Junhong
Adobe PDF(809Kb)  |  收藏  |  浏览/下载：277/43  |  提交时间：2016/01/18
Approximate Policy Iteration  Approximation Error  Optimal Control  Fuzzy Approximator  
A data-based online reinforcement learning algorithm satisfying probably approximately correct principle 期刊论文
NEURAL COMPUTING & APPLICATIONS, 2015, 卷号: 26, 期号: 4, 页码: 775-787
作者:  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(1331Kb)  |  收藏  |  浏览/下载：286/64  |  提交时间：2015/09/21
Reinforcement Learning  Probably Approximately Correct  Kd-tree  
MEC-A Near-Optimal Online Reinforcement Learning Algorithm for Continuous Deterministic Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 2, 页码: 346-356
作者:  Zhao, Dongbin;  Zhu, Yuanheng
浏览  |  Adobe PDF(2156Kb)  |  收藏  |  浏览/下载：300/118  |  提交时间：2015/09/18
Efficient Exploration  Probably Approximately Correct (Pac)  Reinforcement Learning (Rl)  State Aggregation