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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
Adobe PDF(2838Kb)  |  收藏  |  浏览/下载：228/4  |  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：340/50  |  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  
Dynamic Collaborative Tracking 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 10, 页码: 3035-3046
作者:  Zhu, Guibo;  Zhang, Zhaoxiang;  Wang, Jinqiao;  Wu, Yi;  Lu, Hanqing
Adobe PDF(2492Kb)  |  收藏  |  浏览/下载：519/157  |  提交时间：2018/10/11
Correlation filter (CF)  distracter suppression  online learning  visual tracking