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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：250/12  |  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  
Enhanced Rolling Horizon Evolution Algorithm With Opponent Model Learning: Results for the Fighting Game AI Competition 期刊论文
IEEE TRANSACTIONS ON GAMES, 2023, 卷号: 5, 期号: 1, 页码: 5 - 15
作者:  Zhentao Tang;  Yuanheng Zhu;  Dongbin Zhao;  Simon M. Lucas
Adobe PDF(7686Kb)  |  收藏  |  浏览/下载：354/75  |  提交时间：2021/07/05
Rolling horizon evolution  opponent model  reinforcement learning  supervised learning  fighting game  
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：458/136  |  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  
An Incremental Change Detection Test Based on Density Difference Estimation 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 卷号: 49, 期号: 10, 页码: 2714-2726
作者:  Bu, Li;  Zhao, Dongbin;  Alippi, Cesare
浏览  |  Adobe PDF(1601Kb)  |  收藏  |  浏览/下载：454/161  |  提交时间：2017/05/04
Change Detection  Incremental Computing  Incremental Least Squares Density Difference Change Detection Method (Lsdd-inc)  Probability Density Function (Pdf)-free  
A pdf-Free Change Detection Test Based on Density Difference Estimation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 卷号: 29, 期号: 2, 页码: 324-334
作者:  Bu, Li;  Alippi, Cesare;  Zhao, Dongbin
浏览  |  Adobe PDF(2468Kb)  |  收藏  |  浏览/下载：411/119  |  提交时间：2017/05/04
Concept Drift  Least Squares Density-difference (Lsdd)-based Method  Probability Density Function (Pdf)-free  Three-level Threshold Mechanism  
Improved mean shift segmentation approach for natural images 期刊论文
APPLIED MATHEMATICS AND COMPUTATION, 2007, 卷号: 185, 期号: 2, 页码: 940-952
作者:  Hong, Yiping;  Yi, Jianqiang;  Zhao, Dongbin
Adobe PDF(4683Kb)  |  收藏  |  浏览/下载：239/98  |  提交时间：2015/11/08
Natural Image Segmentation  Mean Shift  Mode Detection  Density Estimation