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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：206/0  |  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  
Attention Enhanced Reinforcement Learning for Multi agent Cooperation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 页码: 15
作者:  Pu, Zhiqiang;  Wang, Huimu;  Liu, Zhen;  Yi, Jianqiang;  Wu, Shiguang
Adobe PDF(2967Kb)  |  收藏  |  浏览/下载：312/43  |  提交时间：2022/06/06
Training  Reinforcement learning  Games  Scalability  Task analysis  Standards  Optimization  Attention mechanism  deep reinforcement learning (DRL)  graph convolutional networks  multi agent systems  
Optimal Elevator Group Control via Deep Asynchronous Actor-Critic Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 12, 页码: 5245-5256
作者:  Wei, Qinglai;  Wang, Lingxiao;  Liu, Yu;  Polycarpou, Marios M.
Adobe PDF(4019Kb)  |  收藏  |  浏览/下载：335/76  |  提交时间：2021/03/08
Elevators  Optimal control  Backpropagation  Machine learning  Neural networks  Learning (artificial intelligence)  Actor  –critic  adaptive dynamic programming  deep learning (DL)  elevator group control (EGC)  optimal control  reinforcement learning (RL)  
Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 卷号: 31, 期号: 6, 页码: 2064-2076
作者:  Li, Haoran;  Zhang, Qichao;  Zhao, Dongbin
浏览  |  Adobe PDF(4274Kb)  |  收藏  |  浏览/下载：369/114  |  提交时间：2020/08/03
Robot sensing systems  Navigation  Entropy  Neural networks  Task analysis  Planning  Automatic exploration  deep reinforcement learning (DRL)  optimal decision  partial observation