CASIA OpenIR
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Deep Reinforcement Learning-Based Driving Policy at Intersections Utilizing Lane Graph Networks 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2024, 页码: 1 - 16
作者:  Liu, Yuqi;  Zhang, Qichao;  Gao, Yinfeng;  Zhao, Dongbin
Adobe PDF(22863Kb)  |  收藏  |  浏览/下载:6/2  |  提交时间:2024/06/03
Reinforcement Learning  Autonomous Driving  Intersection Navigating  
Missile guidance with assisted deep reinforcement learning for head-on interception of maneuvering target 期刊论文
COMPLEX & INTELLIGENT SYSTEMS, 2021, 页码: 12
作者:  Li, Weifan;  Zhu, Yuanheng;  Zhao, Dongbin
Adobe PDF(1431Kb)  |  收藏  |  浏览/下载:294/54  |  提交时间:2021/12/28
Reinforcement learning  Missile guidance  Auxiliary learning  Self-imitation learning  
Optimal Feedback Control of Pedestrian Flow in Heterogeneous Corridors 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2021, 卷号: 18, 期号: 3, 页码: 1097-1108
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
Adobe PDF(2666Kb)  |  收藏  |  浏览/下载:195/2  |  提交时间:2021/08/15
Microscopy  Feedback control  Mathematical model  Data models  Dynamic programming  Psychology  Computational modeling  Adaptive dynamic programming (ADP)  heterogeneous corridors  macroscopic pedestrian dynamics  optimal feedback control  pedestrian flow  
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:282/66  |  提交时间:2021/07/05
Rolling horizon evolution  opponent model  reinforcement learning  supervised learning  fighting game  
LMI-Based Synthesis of String-Stable Controller for Cooperative Adaptive Cruise Control 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 卷号: 21, 期号: 11, 页码: 4516-4525
作者:  Zhu, Yuanheng;  He, Haibo;  Zhao, Dongbin
Adobe PDF(1648Kb)  |  收藏  |  浏览/下载:157/4  |  提交时间:2021/01/06
Cooperative adaptive cruise control  string stability  time-delay system  H-infinity control  linear matrix inequality  
MGRL: Graph neural network based inference in a Markov network with Reinforcement Learning for visual navigation 期刊论文
Neurocomputing, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Lu, Yi;  Chen, Yaran;  Zhao, Dongbin;  Li, Dong
Adobe PDF(976Kb)  |  收藏  |  浏览/下载:262/76  |  提交时间:2020/10/19
Visual navigation, graph neural network, Markov network, reinforcement learning, probabilistic graph model  
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
Adobe PDF(4274Kb)  |  收藏  |  浏览/下载:385/117  |  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  
Synthesis of Cooperative Adaptive Cruise Control With Feedforward Strategies 期刊论文
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 卷号: 69, 期号: 4, 页码: 3615-3627
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo
Adobe PDF(2462Kb)  |  收藏  |  浏览/下载:171/4  |  提交时间:2020/06/22
Cooperative cruise control  H-infinity-norm  L-2-gain  time-delay system  state-space model  
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
Adobe PDF(1021Kb)  |  收藏  |  浏览/下载:433/128  |  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  
Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving 期刊论文
IEEE Computational Intelligence Magazine, IEEE Computational Intelligence Magazine, 2019, 2019, 卷号: 14, 14, 期号: 2, 页码: 83-98, 83-98
作者:  Dong Li;  Dongbin Zhao;  Qichao Zhang;  Yaran Chen
浏览  |  Adobe PDF(2205Kb)  |  收藏  |  浏览/下载:374/107  |  提交时间:2019/04/25
Deep Learning  Autonomous Driving  Visual Control  Reinforcement Learning  Deep Learning  Autonomous Driving  Visual Control  Reinforcement Learning