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赵冬斌 [12]

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	NeuronsMAE: A Novel Multi-Agent Reinforcement Learning Environment for Cooperative and Competitive Multi-Robot Tasks 会议论文 , Queensland, Australia, 2023-6 作者: Hu GZ(胡光政); Li HR(李浩然); Liu SS(刘莎莎); Zhu YH(朱圆恒); Zhao DB(赵冬斌) Adobe PDF(2785Kb) \| 收藏 \| 浏览/下载：41/11 \| 提交时间：2024/07/04
	FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game 期刊论文 IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, 页码: 1-13 作者: Guangzheng Hu; Yuanheng Zhu; Haoran Li; Dongbin Zhao Adobe PDF(2144Kb) \| 收藏 \| 浏览/下载：52/11 \| 提交时间：2024/06/05 Games Q-learning Task analysis Optimization Convergence Training Nash equilibrium Multi-agent reinforcement learning minimax-Q learning two-team zero-sum Markov games
	NVIF: Neighboring Variational Information Flow for Cooperative Large-Scale Multiagent Reinforcement Learning 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 页码: 13 作者: Chai, Jiajun; Zhu, Yuanheng; Zhao, Dongbin Adobe PDF(2469Kb) \| 收藏 \| 浏览/下载：66/5 \| 提交时间：2023/11/16 Large-scale multiagent neighboring communication reinforcement learning (RL) variational information flow
	A Hierarchical Deep Reinforcement Learning Framework for 6-DOF UCAV Air-to-Air Combat 期刊论文 IEEE Transactions on Systems, Man and Cybernetics: Systems, 2023, 页码: DOI: 10.1109/TSMC.2023.3270444 作者: Jiajun Chai; Wenzhang Chen; Yuanheng Zhu; Zong-xin Yao,; Dongbin Zhao Adobe PDF(9249Kb) \| 收藏 \| 浏览/下载：299/130 \| 提交时间：2023/04/26
	StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning 期刊论文 IEEE Transactions on Emerging Topics in Computational Intelligence, 2019, 卷号: 3, 期号: 1, 页码: 73-84 作者: Kun Shao; Yuanheng Zhu; Dongbin Zhao Adobe PDF(4125Kb) \| 收藏 \| 浏览/下载：368/138 \| 提交时间：2019/04/22 Reinforcement Learning, Transfer Learning, Curriculum Learning, Neural Network, Game Ai
	Event-Triggered Adaptive Dynamic Programming for Uncertain Nonlinear Systems 会议论文 , Beijing, China, November 19–23 作者: Zhang,Qichao; Zhao,Dongbin; Wang,Ding 浏览 \| Adobe PDF(153Kb) \| 收藏 \| 浏览/下载：219/91 \| 提交时间：2017/12/28
	Off-Policy Reinforcement Learning for Partially Unknown Nonzero-Sum Games 会议论文 , Guangzhou China, November 14–18 作者: Zhang,Qichao; Zhao,Dongbin; Zhang,Sibo 浏览 \| Adobe PDF(119Kb) \| 收藏 \| 浏览/下载：283/109 \| 提交时间：2017/12/28
	Online reinforcement learning for continuous-state systems 专著章节/文集论文出自: Frontiers of Intelligent Control and Information Processing, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore, Singapore:World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, 2014 作者: Yuanheng Zhu; Zhao DB(赵冬斌) Adobe PDF(24150Kb) \| 收藏 \| 浏览/下载：286/38 \| 提交时间：2017/09/13
	Event-triggered adaptive dynamic programming for uncertain nonlinear systems 会议论文 , Beijing, China, 2016-12 作者: Zhang, Qichao; Zhao, Dongbin; Wang, Ding 浏览 \| Adobe PDF(153Kb) \| 收藏 \| 浏览/下载：215/117 \| 提交时间：2017/05/04
	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：576/251 \| 提交时间：2017/05/04 Concurrent Learning Event-triggered Control H-infinity Optimal Control Neural Networks (Nns) Zero-sum (Zs) Game

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