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Data-Based Reinforcement Learning for Nonzero-Sum Games With Unknown Drift Dynamics 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 期号: 8, 页码: 2874-2885
作者:  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(1021Kb)  |  收藏  |  浏览/下载：400/119  |  提交时间：2019/07/12
Integral reinforcement learning (IRL)  neural network (NN)  nonzero-sum (NZS) games  off-policy  single-critic  unknown drift dynamics  
Adaptive Critic Nonlinear Robust Control: A Survey 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3429-3451
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
浏览  |  Adobe PDF(1954Kb)  |  收藏  |  浏览/下载：405/142  |  提交时间：2018/03/03
Adaptive Critic Designs  Adaptive/approximate Dynamic Programming (Adp)  Boundedness  Convergence  Neural Networks  Optimal Control  Reinforcement Learning  Robust Control  Stability  
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3341-3354
作者:  Luo, Biao;  Liu, Derong;  Wu, Huai-Ning;  Wang, Ding;  Lewis, Frank L.
浏览  |  Adobe PDF(3217Kb)  |  收藏  |  浏览/下载：569/204  |  提交时间：2016/11/09
Adaptive Control  Adaptive Dynamic Programming (Adp)  Data-based  Off-policy Learning  Optimal Control  Policy Gradient  
Improving the Critic Learning for Event-Based Nonlinear H-infinity Control Design 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2017, 卷号: 47, 期号: 10, 页码: 3417-3428
作者:  Wang, Ding;  He, Haibo;  Liu, Derong
浏览  |  Adobe PDF(1068Kb)  |  收藏  |  浏览/下载：412/109  |  提交时间：2018/03/03
H-infinity Control  Adaptive Systems  Adaptive/approximate Dynamic Programming  Critic Network  Event-based Design  Learning Criterion  Neural Control  
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 3, 页码: 840-853
作者:  Wei, Qinglai;  Liu, Derong;  Lin, Hanquan;  Derong Liu
浏览  |  Adobe PDF(2015Kb)  |  收藏  |  浏览/下载：371/162  |  提交时间：2016/06/14
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Neural Networks  Neuro-dynamic Programming  Optimal Control  Reinforcement Learning  Value Iteration  
Experience Replay for Optimal Control of Nonzero-Sum Game Systems With Unknown Dynamics 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 卷号: 46, 期号: 3, 页码: 854-865
作者:  Zhao, Dongbin;  Zhang, Qichao;  Wang, Ding;  Zhu, Yuanheng
浏览  |  Adobe PDF(1769Kb)  |  收藏  |  浏览/下载：492/191  |  提交时间：2016/06/14
Adaptive Dynamic Programming (Adp)  Experience Replay  Nonzero-sum (Nzs) Games  Optimal Control  Unknown Dynamics  
Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2015, 卷号: 45, 期号: 7, 页码: 1372-1385
作者:  Liu, Derong;  Yang, Xiong;  Wang, Ding;  Wei, Qinglai
浏览  |  Adobe PDF(1179Kb)  |  收藏  |  浏览/下载：465/242  |  提交时间：2015/09/17
Approximate Dynamic Programming (Adp)  Neural Networks (Nns)  Neuro-dynamic Programming  Nonlinear Systems  Optimal Control  Reinforcement Learning (Rl)  Robust Control  
Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2014, 卷号: 44, 期号: 12, 页码: 2834-2847
作者:  Liu, Derong;  Wang, Ding;  Wang, Fei-Yue;  Li, Hongliang;  Yang, Xiong
浏览  |  Adobe PDF(780Kb)  |  收藏  |  浏览/下载：437/204  |  提交时间：2015/08/12
Adaptive Critic Designs  Adaptive/approximate Dynamic Programming (Adp)  Hamilton-jacobi-bellman (Hjb) Equation  Neural Networks  Optimal Robust Guaranteed Cost Control  Uncertain Nonlinear Systems  
Finite-Approximation-Error-Based Discrete-Time Iterative Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2014, 卷号: 44, 期号: 12, 页码: 2820-2833
作者:  Wei, Qinglai;  Wang, Fei-Yue;  Liu, Derong;  Yang, Xiong
浏览  |  Adobe PDF(1826Kb)  |  收藏  |  浏览/下载：293/109  |  提交时间：2015/08/12
Adaptive Critic Designs  Adaptive Dynamic Programming (Adp)  Approximate Dynamic Programming  Approximation Error  Neural Networks  Neuro-dynamic Programming  Nonlinear Systems  Optimal Control  Reinforcement Learning  Value Iteration