CASIA OpenIR
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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:World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, World Scientific, 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:245/27  |  提交时间:2017/09/13
An high-efficient online reinforcement learning algorithm for continuous-state systems 会议论文
IEEE World Congresson Intelligent Control and Automation (WCICA), Shenyang, China, 2014
作者:  Yuanheng Zhu;  Dongbin Zhao;  Haibo He
浏览  |  Adobe PDF(764Kb)  |  收藏  |  浏览/下载:249/79  |  提交时间:2015/08/19
Event-triggered reinforcement learning approach for unknown nonlinear continuous-time system 会议论文
International Joint Conference on Neural Networks (IJCNN), 2014
作者:  Xiangnan Zhong;  Zhen Ni;  Haibo He;  Xin Xu;  Dongbin Zhao
收藏  |  浏览/下载:269/0  |  提交时间:2015/08/19
Detecting and Reacting to Changes in Sensing Units: The Active Classifier Case 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2014, 卷号: 44, 期号: 3, 页码: 353-362
作者:  Alippi, Cesare;  Liu, Derong;  Zhao, Dongbin;  Bu, Li
浏览  |  Adobe PDF(444Kb)  |  收藏  |  浏览/下载:206/53  |  提交时间:2015/08/12
Active Classifiers  Change Detection Tests (Cdts)  Intelligent Sensing  K-nearest Neighbor  Support Vector Machine (Svm) Classifiers