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An Improved Minimax-Q Algorithm Based on Generalized Policy Iteration to Solve a Chaser-Invader Game 会议论文
, 线上, 2020-5
作者:  Liu MS(刘民颂);  Zhu YH(朱圆恒);  Zhao DB(赵冬斌)
Adobe PDF(727Kb)  |  收藏  |  浏览/下载：25/11  |  提交时间：2024/07/04
Enhancing Reinforcement Learning via Transformer-based State Predictive Representations 期刊论文
IEEE Transactions on Artificial Intelligence, 2024, 页码: 1 - 12
作者:  Liu MS(刘民颂);  Zhu YH(朱圆恒);  Chen YR(陈亚冉);  Zhao DB(赵冬斌)
Adobe PDF(1162Kb)  |  收藏  |  浏览/下载：33/9  |  提交时间：2024/06/24
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：46/9  |  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  
Advantage Constrained Proximal Policy Optimization in Multi-Agent Reinforcement Learning 会议论文
, 昆士兰, 2023-6
作者:  Li WF(李伟凡);  Zhu YH(朱圆恒);  Zhao DB(赵冬斌)
Adobe PDF(4104Kb)  |  收藏  |  浏览/下载：261/81  |  提交时间：2023/06/29
multi-agent  reinforcement learning  policy gradient  
Multi-Agent Reinforcement Learning Based on Clustering in Two-Player Games 会议论文
, Xiamen, China, 2019-12-6
作者:  Li WF(李伟凡);  Zhu YH(朱圆恒);  Zhao DB(赵冬斌)
Adobe PDF(488Kb)  |  收藏  |  浏览/下载：156/49  |  提交时间：2023/06/28
reinforcement learning  unsupervised clustering  matrix game  
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：294/128  |  提交时间：2023/04/26
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：256/13  |  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  
Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 页码: 13
作者:  Hu, Guangzheng;  Zhu, Yuanheng;  Zhao, Dongbin;  Zhao, Mengchen;  Hao, Jianye
Adobe PDF(4187Kb)  |  收藏  |  浏览/下载：266/12  |  提交时间：2022/01/27
Bandwidth  Protocols  Reinforcement learning  Task analysis  Optimization  Communication networks  Multi-agent systems  Event trigger  limited bandwidth  multi-agent communication  multi-agent reinforcement learning (MARL)  
Adaptive Optimal Control of Heterogeneous CACC System With Uncertain Dynamics 期刊论文
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2019, 卷号: 27, 期号: 4, 页码: 1772-1779
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  Zhong, Zhiguang
Adobe PDF(1189Kb)  |  收藏  |  浏览/下载：293/16  |  提交时间：2019/09/30
Adaptive optimal control  cooperative adaptive cruise control (CACC)  heterogeneous platoon  string stability  sum-of-squares polynomial  
An Autonomous Driving Experience Platform with Learning-Based Functions 会议论文
, Bangalore, India, 18-21 Nov. 2018
作者:  Li, Dong;  Zhao, Dongbin;  Zhang, Qichao;  Zhu, Yuanheng
浏览  |  Adobe PDF(215Kb)  |  收藏  |  浏览/下载：308/77  |  提交时间：2019/04/25