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检索条件"任意字段=IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning"
1015 条 记 录,以下是371-380 订阅
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Self-learning Control Using Dual Heuristic programming with Global Laplacian Eigenmaps
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ieee TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2017年 第12期64卷 9517-9526页
作者: Xu, Xin Yang, Huiyuan Lian, Chuanqiang Liu, Jiahang Natl Univ Def Technol Inst Unmanned Syst Coll Intelligence Sci Changsha 410073 Hunan Peoples R China
In this paper, to solve nonlinear optimal control problems which can be modeled as Markov decision processes (MDPs), we present an online self-learning control algorithm called dual heuristic programming with global L... 详细信息
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Evaluation of policy gradient methods and variants on the cart-pole benchmark
Evaluation of policy gradient methods and variants on the ca...
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ieee International symposium on Approximate dynamic programming and reinforcement learning
作者: Riedmiller, Martin Peters, Jan Schaal, Stefan Univ Osnabruck Neuroinformat Grp D-4500 Osnabruck Germany Univ Southern Calif Computat Learning & Motor Control Los Angeles CA 90007 USA
In this paper, we evaluate different versions from the three main kinds of model-free policy gradient methods, i.e., finite difference gradients, 'vanilla' policy gradients and natural policy gradients. Each o... 详细信息
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An Online reinforcement learning Wing-Tracking Mechanism for Flexible Wing Aircraft  13
An Online Reinforcement Learning Wing-Tracking Mechanism for...
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13th ieee International symposium on Robotic and Sensors Environments (ROSE)
作者: Abouheaf, Mohammed Mailhot, Nathaniel Gueaieb, Wail Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Aswan Univ Coll Energy Engn Aswan Egypt Univ Ottawa Dept Mech Engn Ottawa ON Canada
Flexible wing aircraft are gaining an increasing interest due to their salient features, such as inexpensive market price, low-cost operation, in-flight robustness, multi-purpose use, and their ability to operate with... 详细信息
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learning to Regulate Rolling Ball Motion
Learning to Regulate Rolling Ball Motion
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ieee symposium Series on Computational Intelligence (ieee SSCI)
作者: Jha, Devesh K. Yerazunis, William Nikovski, Daniel Farahmand, Amir-massoud Mitsubishi Elect Res Labs Cambridge MA 02139 USA
In this paper, we present a problem of regulating the motion of a rolling ball in a one-dimensional space in the presence of non-linear effects of friction and contact. The regulation problem is solved using a model-b... 详细信息
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Annealing-Pareto Multi-Objective Multi-Armed Bandit Algorithm
Annealing-Pareto Multi-Objective Multi-Armed Bandit Algorith...
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ieee symposium on adaptive dynamic programming and reinforcement learning (ADPRL)
作者: Yahyaa, Saba Q. Drugan, Madalina M. Manderick, Bernard Vrije Univ Brussel Dept Comp Sci Pl Laan 2 B-1050 Brussels Belgium
In the stochastic multi-objective multi-armed bandit (or MOMAB), arms generate a vector of stochastic rewards, one per objective, instead of a single scalar reward. As a result, there is not only one optimal arm, but ... 详细信息
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Intelligent Energy Management Strategy Based on an Improved reinforcement learning Algorithm With Exploration Factor for a Plug-in PHEV
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ieee TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年 第7期23卷 8725-8735页
作者: Lin, Xinyou Zhou, Kuncheng Mo, Liping Li, Hailin Fuzhou Univ Coll Mech Engn & Automat Fuzhou 350108 Peoples R China West Virginia Univ Dept Mech & Aerosp Engn Morgantown WV 26506 USA
An intelligent energy management strategy (EMS) based on an improved reinforcement learning (RL) algorithm is developed to enhance the adaptability of the EMS and to further improve the fuel efficiency of a Plug-in Pa... 详细信息
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Short-term stock market timing prediction under reinforcement learning schemes
Short-term stock market timing prediction under reinforcemen...
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2007 ieee symposium on Approximate dynamic programming and reinforcement learning, ADPRL 2007
作者: Hailin, Li Dagli, Cihan H. Enke, David Department of Engineering Management and Systems Engineering University of Missouri-Rolla Rolla MO 65409-0370 United States
There are fundamental difficulties when only using a supervised learning philosophy to predict financial stock short-term movements. We present a reinforcement-oriented forecasting framework in which the solution is c... 详细信息
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reinforcement learning for adaptive Periodic Linear Quadratic Control  58
Reinforcement Learning for Adaptive Periodic Linear Quadrati...
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58th ieee Conference on Decision and Control (CDC)
作者: Pang, Bo Jiang, Zhong-Ping Mareels, Iven NYU Tandon Sch Engn Dept Elect & Comp Engn Control & Networks LabMetrotech Ctr 6 Brooklyn NY 11201 USA IBM Res Australia Melbourne Vic 3006 Australia
This paper presents a first solution to the problem of adaptive LQR for continuous-time linear periodic systems. Specifically, reinforcement learning and adaptive dynamic programming (ADP) techniques are used to devel... 详细信息
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Approximate dynamic programming Solutions of Multi-Agent Graphical Games Using Actor-Critic Network Structures
Approximate Dynamic Programming Solutions of Multi-Agent Gra...
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International Joint Conference on Neural Networks (IJCNN)
作者: Abouheaf, Mohammed I. Lewis, Frank L. Univ Texas Arlington Res Inst Ft Worth TX 76118 USA
This paper studies a new class of multi-agent discrete-time dynamical graphical games, where interactions between agents are restricted by a communication graph structure. The paper brings together discrete Hamiltonia... 详细信息
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Disturbance-Aware Neuro-Optimal System Control Using Generative Adversarial Control Networks
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning SYSTEMS 2021年 第10期32卷 4565-4576页
作者: Chu, Kai-Fung Lam, Albert Y. S. Fan, Chenchen Li, Victor O. K. Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Univ Hong Kong Shenzhen Inst Res & Innovat Hong Kong Peoples R China Fano Labs Hong Kong Peoples R China Univ Hong Kong Dept Mech Engn Hong Kong Peoples R China
Disturbance, which is generally unknown to the controller, is unavoidable in real-world systems and it may affect the expected system state and output. Existing control methods, like robust model predictive control, c... 详细信息
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