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检索条件"任意字段=IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning"
1027 条 记 录,以下是741-750 订阅
Optimal Control for a Class of Unknown Nonlinear Systems via the Iterative GDHP Algorithm
Optimal Control for a Class of Unknown Nonlinear Systems via...
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8th International symposium on Neural Networks
作者: Wang, Ding Liu, Derong Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China
Using the neural-network-based iterative adaptive dynamic programming (ADP) algorithm, an optimal control scheme for a class of unknown discrete-time nonlinear systems with discount factor in the cost function is prop... 详细信息
来源: 评论
adaptive Dual Heuristic programming Based on Delta-Bar-Delta learning Rule
Adaptive Dual Heuristic Programming Based on Delta-Bar-Delta...
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8th International symposium on Neural Networks
作者: Wu, Jun Xu, Xin Lian, Chuanqiang Huang, Yan Natl Univ Def Technol Coll Mechatron & Automat Inst Automat Changsha 410073 Hunan Peoples R China
Dual Heuristic programming (DHP) is a class of approximate dynamic programming methods using neural networks. Although there have been some successful applications of DHP, its performance and convergence are greatly i... 详细信息
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reinforcement learning with adaptive Kanerva Coding for Xpilot Game AI
Reinforcement Learning with Adaptive Kanerva Coding for Xpil...
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ieee Congress on Evolutionary Computation (CEC)
作者: Allen, Martin Fritzsche, Phil Univ Wisconsin Dept Comp Sci La Crosse WI 54601 USA Coll New London Comp Sci Dept Connecticut New London CT USA
The Xpilot-AI video game platform allows the creation of artificially intelligent and autonomous control agents. At the same time, the Xpilot environment is highly complex, with very many state variables and action ch... 详细信息
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A new approach for power management in sensor node based on reinforcement learning
A new approach for power management in sensor node based on ...
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International symposium on Computer Networks and Distributed Systems
作者: Kianpisheh, Somayeh Charkari, Nasrolah Moghadam Faculty of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran
Wireless sensor networks are composed of small nodes with limited battery life and computational ability. Energy reduction in these networks is an important issue to extend network lifetime. dynamic power management i... 详细信息
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Hierarchical Approximate Policy Iteration with Binary-Tree State Space Decomposition
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ieee TRANSACTIONS ON NEURAL NETWORKS 2011年 第12期22卷 1863-1877页
作者: Xu, Xin Liu, Chunming Yang, Simon X. Hu, Dewen Natl Univ Def Technol Coll Mechatron & Automat Changsha 410073 Hunan Peoples R China Univ Guelph Sch Engn Guelph ON N1G 2W1 Canada
In recent years, approximate policy iteration (API) has attracted increasing attention in reinforcement learning (RL), e. g., least-squares policy iteration (LSPI) and its kernelized version, the kernel-based LSPI alg... 详细信息
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Bayesian active learning with basis functions
Bayesian active learning with basis functions
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ieee symposium on adaptive dynamic programming and reinforcement learning, (ADPRL)
作者: Ilya O. Ryzhov Warren B. Powell Operations Research and Financial Engineering Princeton University Princeton NJ USA
A common technique for dealing with the curse of dimensionality in approximate dynamic programming is to use a parametric value function approximation, where the value of being in a state is assumed to be a linear com... 详细信息
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adaptive dynamic programming with balanced weights seeking strategy
Adaptive dynamic programming with balanced weights seeking s...
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ieee symposium on adaptive dynamic programming and reinforcement learning, (ADPRL)
作者: Jian Fu Haibo He Zhen Ni School of Automation Wuhan University of Technology Wuhan Hubei China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA
In this paper we propose to integrate the recursive Levenberg-Marquardt method into the adaptive dynamic programming (ADP) design for improved learning and adaptive control performance. Our key motivation is to consid... 详细信息
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Feedback controller parameterizations for reinforcement learning
Feedback controller parameterizations for Reinforcement Lear...
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ieee symposium on adaptive dynamic programming and reinforcement learning, (ADPRL)
作者: John W. Roberts Ian R. Manchester Russ Tedrake MIT CSAIL Cambridge MA USA
reinforcement learning offers a very general framework for learning controllers, but its effectiveness is closely tied to the controller parameterization used. Especially when learning feedback controllers for weakly ... 详细信息
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adaptive dynamic programming for optimal control of unknown nonlinear discrete-time systems
Adaptive dynamic programming for optimal control of unknown ...
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ieee symposium on adaptive dynamic programming and reinforcement learning, (ADPRL)
作者: Derong Liu Ding Wang Dongbin Zhao Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China
An intelligent optimal control scheme for unknown nonlinear discrete-time systems with discount factor in the cost function is proposed in this paper. An iterative adaptive dynamic programming (ADP) algorithm via glob... 详细信息
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Supervised adaptive dynamic programming based adaptive cruise control
Supervised adaptive dynamic programming based adaptive cruis...
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ieee symposium on adaptive dynamic programming and reinforcement learning, (ADPRL)
作者: Dongbin Zhao Zhaohui Hu Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China
This paper proposes a supervised adaptive dynamic programming (SADP) algorithm for the full range adaptive cruise control (ACC) system. The full range ACC system considers both the ACC situation in highway system and ... 详细信息
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