CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共28条,第1-10条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Driving Control with Deep and Reinforcement Learning in The Open Racing Car Simulator 会议论文
, Siem Reap, Cambodia, 2018, 12, 13-16
作者:  Yuanheng Zhu;  Dongbin Zhao
Adobe PDF(697Kb)  |  收藏  |  浏览/下载:7/2  |  提交时间:2024/06/05
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:2/1  |  提交时间:2024/06/03
Reinforcement Learning  Autonomous Driving  Intersection Navigating  
Optimal Pedestrian Evacuation in Building with Consecutive Differential Dynamic Programming 会议论文
, Budapest, Hungary, 2019-7-14
作者:  Zhu YH(朱圆恒);  Haibo He;  Dongbin Zhao;  Zhongsheng Hou
Adobe PDF(679Kb)  |  收藏  |  浏览/下载:63/31  |  提交时间:2023/05/22
Vision-based control in the open racing car simulator with deep and reinforcement learning 期刊论文
Journal of Ambient Intelligence and Humanized Computing, 2019, 页码: doi={10.1007/s12652-019-01503-y}
作者:  Yuanheng Zhu;  Dongbin Zhao
Adobe PDF(2210Kb)  |  收藏  |  浏览/下载:51/12  |  提交时间:2023/04/26
Empirical Policy Optimization for n-Player Markov Games 期刊论文
IEEE Transactions on Cybernetics, 2022, 页码: doi={10.1109/TCYB.2022.3179775}
作者:  Yuanheng Zhu;  Weifan Li;  Mengchen Zhao;  Jianye Hao;  Dongbin Zhao
Adobe PDF(1739Kb)  |  收藏  |  浏览/下载:98/39  |  提交时间:2023/04/26
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:191/1  |  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  
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:428/127  |  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  
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
Adobe PDF(153Kb)  |  收藏  |  浏览/下载:199/81  |  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:253/27  |  提交时间:2017/09/13
Event-Triggered Optimal Control for Partially Unknown Constrained-Input Systems via Adaptive Dynamic Programming 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 卷号: 64, 期号: 5, 页码: 4101-4109
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  He, Haibo;  Ji, Junhong
Adobe PDF(2325Kb)  |  收藏  |  浏览/下载:539/211  |  提交时间:2017/09/12
Actor-critic-identifier  Concurrent Learning  Constrained Input  Event-triggered (Et) Control  Hamilton-jacobi-bellman (Hjb) Equation