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检索条件"主题词=Dyna-Q algorithm"
6 条 记 录,以下是1-10 订阅
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dyna-q algorithm for Path Planning of quadrotor UAVs  18th
Dyna-Q Algorithm for Path Planning of Quadrotor UAVs
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18th Annual Asia Simulation Conference (AsiaSim)
作者: Huo, Xin Zhang, Tianze Wang, Yuzhu Liu, Weizhen Harbin Inst Technol Harbin 150080 Peoples R China Natl Instruments China Shanghai 201203 Peoples R China Helong Senior High Sch Nongan Changchun 130216 Peoples R China
In this paper, the problem of path planning of quadrotor unmanned aerial vehicles (UAVs) is investigated in the framework of reinforcement learning methodology. With the abstraction of the environment in the form of g... 详细信息
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Autonomous PEV Charging Scheduling Using dyna-q Reinforcement Learning
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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2020年 第11期69卷 12609-12620页
作者: Wang, Fan Gao, Jie Li, Mushu Zhao, Lian Bell Canada Business Intelligence Dept Toronto ON M3C 4B4 Canada Marquette Univ Dept Elect & Comp Engn Milwaukee WI 53233 USA Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Ryerson Univ Dept Elect Comp & Biomed Engn Toronto ON M5B 2K3 Canada
This paper proposes a demand response method to reduce the long-term charging cost of single plug-in electric vehicles (PEV) while overcoming obstacles such as the stochastic nature of the user's driving behaviour... 详细信息
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dyna-q-based vector direction for path planning problem of autonomous mobile robots in unknown environments
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ADVANCED ROBOTICS 2013年 第3期27卷 159-173页
作者: Hoang Huu Viet An, Sang Hyeok Chung, Tae Choong Kyung Hee Univ Dept Comp Engn Yongin 446701 Gyeonggi South Korea
Reinforcement learning (RL) is a popular method for solving the path planning problem of autonomous mobile robots in unknown environments. However, the primary difficulty faced by learning robots using the RL method i... 详细信息
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Reinforcement Learning Combined with Heuristic Search for Solving Discrete Space Path Planning Problems  33
Reinforcement Learning Combined with Heuristic Search for So...
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33rd Chinese Control and Decision Conference (CCDC)
作者: Zhang, Xiuling Kang, Xuenan Wei, Kailun Li, Jinxiang Ma, Kai Yanshan Univ Engn Res Ctr Minist Educ Intelligent Control Syst & Intelligen Qinhuangdao 066004 Hebei Peoples R China Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao 066004 Hebei Peoples R China
Reinforcement learning (RL) has been successfully applied to solve path planning problems, but learning is generally slow. The main reason is not making full use of information collected during interaction with the en... 详细信息
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On-line reinforcement learning control for urban traffic signals
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26th Chinese Control Conference
作者: Liu Zhi-Yong Ma Feng-Wei Wuyi Univ Informat Sch Jiangmen 529020 Guangdong Peoples R China
It is quit difficult to archive perfect effects by applying the traditional modeling and control methods-to the urban traffic signal control system because of non-linearity, fuzzyness, self-organization and uncertaint... 详细信息
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Reinforcement Learning Combined with Heuristic Search for Solving Discrete Space Path Planning Problems
Reinforcement Learning Combined with Heuristic Search for So...
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第33届中国控制与决策会议
作者: Xiuling Zhang Xuenan Kang Kailun Wei Jinxiang Li Kai Ma Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University
Reinforcement learning(RL) has been successfully applied to solve path planning problems,but learning is generally *** main reason is not making full use of information collected during interaction with the *** paper ... 详细信息
来源: 评论