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检索条件"任意字段=IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning"
1018 条 记 录,以下是391-400 订阅
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adaptive Optimal Control via Continuous-Time Q-learning for Unknown Nonlinear Affine Systems  58
Adaptive Optimal Control via Continuous-Time Q-Learning for ...
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58th ieee Conference on Decision and Control (CDC)
作者: Chen, Anthony Siming Herrmann, Guido Univ Bristol Dept Mech Engn Bristol BS8 1QU Avon England Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL Lancs England
This paper proposes two novel adaptive optimal control algorithms for continuous-time nonlinear affine systems based on reinforcement learning: i) generalised policy iteration (GPI) and ii) Q-learning. As a result, th... 详细信息
来源: 评论
adaptive Data Replication Optimization Based on reinforcement learning
Adaptive Data Replication Optimization Based on Reinforcemen...
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ieee symposium Series on Computational Intelligence (SSCI)
作者: Chee Keong Wee Richi Nayak Digital Application Services Business Applications Technology Services eHealth Queensland Queensland Australia School of Electrical Engineering & Computer Science Science & Engineering Faculty Queensland University of Technology Brisbane Queensland Australia
Data replication plays an important role in enterprise IT landscapes, where data is shared among multiple IT systems. IT administrators need to tune the replicating software's configuration setting for it to perfo... 详细信息
来源: 评论
reinforcement Q-learning Incorporated With Internal Model Method for Output Feedback Tracking Control of Unknown Linear Systems
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ieee ACCESS 2020年 8卷 134456-134467页
作者: Chen, Cong Sun, Weijie Zhao, Guangyue Peng, Yunjian South China Univ Technol Sch Automat Sci & Engn Guangzhou 510640 Peoples R China
This paper investigates the output feedback (OPFB) tracking control problem for discrete-time linear (DTL) systems with unknown dynamics. With the approach of augmented system, the tracking control problem is first tu... 详细信息
来源: 评论
adaptive Critic Designs for Event-Triggered Robust Control of Nonlinear Systems With Unknown dynamics
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ieee TRANSACTIONS ON CYBERNETICS 2019年 第6期49卷 2255-2267页
作者: Yang, Xiong He, Haibo Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Univ Rhode Isl Dept Elect Comp & Biomed Engn Kingston RI 02881 USA
This paper develops a novel event-triggered robust control strategy for continuous-time nonlinear systems with unknown dynamics. To begin with, the event-triggered robust nonlinear control problem is transformed into ... 详细信息
来源: 评论
reinforcement learning for Robotic Safe Control with Force Sensing  2
Reinforcement Learning for Robotic Safe Control with Force S...
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2nd World Robot Conference (WRC) / symposium on Advanced Robotics and Automation (WRC SARA)
作者: Lin, Nan Zhang, Linrui Chen, Yuxuan Zhu, Yujun Chen, Ruoxi Wu, Peichen Chen, Xiaoping Univ Sci & Technol China Sch Comp Sci & Technol Hefei 230026M Peoples R China Sch Informat Sci & Technol China Hefei 230026 Peoples R China
For the task with complicated manipulation in unstructured environments, traditional hand-coded methods are ineffective, while reinforcement learning can provide more general and useful policy. Although the reinforcem... 详细信息
来源: 评论
adaptive Slope Locomotion with Deep reinforcement learning
Adaptive Slope Locomotion with Deep Reinforcement Learning
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ieee/SICE International symposium on System Integration
作者: William Jones Tamir Blum Kazuya Yoshida Space Robotics Laboratory of the Department of Aerospace Engineering Graduate School of Engineering Tohoku University Sendai Japan
In this paper we present a model free Deep reinforcement learning based approach to the motion planning problem of a quadruped moving from a flat to an inclined plane. In our implementation, we do not provide any prio... 详细信息
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Longitudinal dynamic versus Kinematic Models for Car-Following Control Using Deep reinforcement learning
Longitudinal Dynamic versus Kinematic Models for Car-Followi...
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ieee Intelligent Transportation Systems Conference (ieee-ITSC)
作者: Lin, Yuan McPhee, John Azad, Nasser L. Univ Waterloo Syst Design Engn Dept Waterloo ON N2L 3G1 Canada
The majority of current studies on autonomous vehicle control via deep reinforcement learning (DRL) utilize point-mass kinematic models, neglecting vehicle dynamics which includes acceleration delay and acceleration c... 详细信息
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Neural Network Tracking Control of Unknown Servo System with Approximate dynamic programming  38
Neural Network Tracking Control of Unknown Servo System with...
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38th Chinese Control Conference (CCC)
作者: Lv, Yongfeng Ren, Xuemei Zeng, Tianyi Li, Linwei Na, Jing Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Kunming Univ Sci & Technol Fac Mech & Elect Engn Kunming 650500 Yunnan Peoples R China
Although the adaptive dynamic programming (ADP) scheme has been widely researched on the optimal problem in recent years, which has not been applied to the servo system. In this paper, a simplified reinforcement learn... 详细信息
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reinforcement learning for Vision-Based Lateral Control of a Self-Driving Car  15
Reinforcement Learning for Vision-Based Lateral Control of a...
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ieee 15th International Conference on Control and Automation (ICCA)
作者: Huang, Mengzhe Zhao, Mingyu Parikh, Parthiv Wang, Yebin Ozbay, Kaan Jiang, Zhong-Ping NYU Tandon Sch Engn Dept Elect & Comp Engn Brooklyn NY 11201 USA Mitsubishi Elect Res Labs Cambridge MA 02139 USA NYU C2SMART Ctr Tandon Sch Engn Brooklyn NY 11201 USA
Lateral control design is one of the fundamental components for self-driving cars. In this paper, we propose a learning-based control strategy that enables a mobile car equipped with a camera to perfectly perform lane... 详细信息
来源: 评论
Geometric deep reinforcement learning for dynamic DAG scheduling
Geometric deep reinforcement learning for dynamic DAG schedu...
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ieee symposium Series on Computational Intelligence (SSCI)
作者: Nathan Grinsztajn Olivier Beaumont Emmanuel Jeannot Philippe Preux UMR 9189 CRIStAL Univ. Lille CNRS Inria Lille France Hiepacs team Inria Bordeaux Bordeaux France TADaaM team Inria Bordeaux Bordeaux France
In practice, it is quite common to face combinatorial optimization problems which contain uncertainty along with non determinism and dynamicity. These three properties call for appropriate algorithms; reinforcement le... 详细信息
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