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北京航空航天大学 [24]

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限定条件	专题：北京航空航天大学第一署名单位第一作者单位通讯作者单位

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	New insight into the simultaneous policy update algorithms related to H-infinity state feedback control 期刊论文 INFORMATION SCIENCES, 2019, 卷号: 484, 页码: 84-94 作者: Liu, Zhou-Yang; Wu, Huai-Ning 收藏 \| 浏览/下载：17/0 \| 提交时间：2019/12/30 Simultaneous policy update algorithm H-infinity control Continuous-time algebra Riccati equation Kantorovich's theorem Reinforcement learning
	Off-Policy Reinforcement Learning for Optimal Preview Tracking Control of Linear Discrete-Time systems with unknown dynamics 会议论文 Proceedings 2018 Chinese Automation Congress, CAC 2018, 2018-11-30 作者: Wang, C.-R.; Wu, H.-N. 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/30 Digital control systems Machine learning Navigation Reinforcement learning Riccati equations Vector spaces Algebraic Riccati equations Augmented state space Discrete - time systems Linear discrete-time systems Linear quadratic regulator Reinforcement learning techniques Tracking control problem Tracking controls Discrete time control systems
	Ensuring the Safety Sustainability of Large UAS: Learning from the Maintenance Risk Dynamics of USAF MQ-1 Predator Fleet in Last Two Decades 期刊论文 SUSTAINABILITY, 2019, 卷号: 11 作者: Lu, Yi; Qian, Ying; Huangfu, Huayan; Zhang, Shuguang; Fu, Shan 收藏 \| 浏览/下载：14/0 \| 提交时间：2019/12/30 unmanned aerial system safety sustainability risk dynamics modeling policy experiment
	A fuzzy deterministic policy gradient algorithm for pursuit-evasion differential games 期刊论文 NEUROCOMPUTING, 2019, 卷号: 362, 页码: 106-117 作者: Wang, Lixin; Wang, Maolin; Yue, Ting 收藏 \| 浏览/下载：11/0 \| 提交时间：2019/12/30 Fuzzy logic Fuzzy inference system Reinforcement learning Differential game Deterministic policy gradient
	Learning a Hybrid Proactive and Reactive Caching Policy in Wireless Edge Under Dynamic Popularity 期刊论文 IEEE ACCESS, 2019, 卷号: 7, 页码: 120788-120801 作者: Qi, Kaiqiang; Han, Shengqian; Yang, Chenyang 收藏 \| 浏览/下载：2/0 \| 提交时间：2019/12/30 Dynamic popularity proactive and reactive caching cache resource allocation shot noise model independent reference model real datasets
	Reinforcement Learning Policy for Adaptive Edge Caching in Heterogeneous Vehicular Network 会议论文 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings 作者: Chen, J.; Xu, W.; Cheng, N.; Wu, H.; Zhang, S. 收藏 \| 浏览/下载：6/0 \| 提交时间：2019/12/30
	Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo 期刊论文 TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2018, 卷号: 110, 页码: 107-117 作者: Ding, Chuan; Cao, Xinyu; Naess, Petter 收藏 \| 浏览/下载：1/0 \| 提交时间：2019/12/30 Compact development Land use Travel behavior Machine learning Employment center
	Optimal Output Regulation for Model-Free Quanser Helicopter With Multistep Q-Learning 期刊论文 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 卷号: 65, 页码: 4953-4961 作者: Luo, Biao; Wu, Huai-Ning; Huang, Tingwen 收藏 \| 浏览/下载：5/0 \| 提交时间：2019/12/30 Helicopter model-free multistep policy evaluation optimal output regulation Q-learning
	Too Far to See? Not Really!-Pedestrian Detection With Scale-Aware Localization Policy 期刊论文 IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 页码: 3703-3715 作者: Zhang, Xiaowei; Cheng, Li; Li, Bo; Hu, Hai-Miao 收藏 \| 浏览/下载：4/0 \| 提交时间：2019/12/30 Localization policy sequence of coordinate transformations deep reinforcement learning multiple-layer neuronal representations pedestrian object proposals
	Online learning based on a novel cost function for system power management 期刊论文 IET COMPUTERS AND DIGITAL TECHNIQUES, 2018, 卷号: 12, 页码: 227-232 作者: Wang, Xiang; Li, Lin; Wang, Weike; Du, Pei 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/30 learning (artificial intelligence) power aware computing optimisation online learning cost function system power management technique state-action multiple parameter constraints Q-learning rational optimisation room power model power management policy

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