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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
收藏  |  浏览/下载：185/0  |  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 H-infinity Control for Continuous-Time Nonlinear System via Concurrent Learning 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 47, 期号: 7, 页码: 1071-1081
作者:  Zhang, Qichao;  Zhao, Dongbin;  Zhu, Yuanheng
浏览  |  Adobe PDF(2937Kb)  |  收藏  |  浏览/下载：512/238  |  提交时间：2017/05/04
Concurrent Learning  Event-triggered Control  H-infinity Optimal Control  Neural Networks (Nns)  Zero-sum (Zs) Game  
Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 卷号: 28, 期号: 3, 页码: 714-725
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  Li, Xiangjun
浏览  |  Adobe PDF(547Kb)  |  收藏  |  浏览/下载：428/179  |  提交时间：2017/05/05
Adaptive Dynamic Programming (Adp)  H-infinity Control  Policy Iteration (Pi)  Zero-sum Game (Zsg)