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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411-420 订阅
排序:
Block-Decentralized Model-Free reinforcement learning Control of Two Time-Scale Networks
Block-Decentralized Model-Free Reinforcement Learning Contro...
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American Control Conference (ACC)
作者: Mukherjee, Sayak Bai, He Chakrabortty, Aranya North Carolina State Univ Dept Elect & Comp Engn Raleigh NC 27695 USA Oklahoma State Univ Sch Mech & Aerosp Engn Stillwater OK 74078 USA
In this paper, we present a cluster-wise decentralized model-free reinforcement learning (RL) based control design for a linear time-invariant consensus network. We assume that the fast dynamics of the network is stab... 详细信息
来源: 评论
A Service Migration Method Based on dynamic Awareness in Mobile Edge Computing
A Service Migration Method Based on Dynamic Awareness in Mob...
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ieee symposium on Network Operations and Management
作者: Menglei Zhang Haoqiu Huang LanLan Rui Guo Hui Ying Wang Xuesong Qiu State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Information Department China Aerospace Science and Industry Corporation Limited Network Beijing China
Cloud computing technologies can not satisfy the requirements of applications on the mobile terminals because of their disadvantages in delay, link load and energy. So Mobile Edge Computing (MEC) is proposed as a kind...
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Manifold Regularized reinforcement learning
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ieee TRANSACTIONS ON NEURAL NETWORKS AND learning SYSTEMS 2018年 第4期29卷 932-943页
作者: Li, Hongliang Liu, Derong Wang, Ding Tencent Inc AI Platform Dept Shenzhen 518057 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China
This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned u... 详细信息
来源: 评论
AVAC: A Machine learning Based adaptive RRAM Variability-Aware Controller for Edge Devices
AVAC: A Machine Learning Based Adaptive RRAM Variability-Awa...
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ieee International symposium on Circuits and Systems (ISCAS)
作者: Shikhar Tuli Shreshth Tuli Department of Electrical Engineering Indian Institute of Technology Delhi Department of Computer Science and Engineering Indian Institute of Technology Delhi
Recently, the Edge Computing paradigm has gained significant popularity both in industry and academia. Researchers now increasingly target to improve performance and reduce energy consumption of such devices. Some rec... 详细信息
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learning Run-Time Compositions of Interacting Adaptations
Learning Run-Time Compositions of Interacting Adaptations
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SEAMS International Workshop on Software Engineering for adaptive and Self-Managing Systems, ICSE
作者: Nicolás Cardozo Ivana Dusparic Systems and Computing Engineering Department Universidad de los Andes Colombia School of Computer Science and Statistics Trinity College Dublin Ireland
Self-adaptive systems continuously adapt to internal and external changes in their execution environment. In context-based self-adaptation, adaptations take place in response to the characteristics of the execution en...
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A dynamic Energy-saving Deployment Algorithm for Virtual Data Centers  4
A Dynamic Energy-saving Deployment Algorithm for Virtual Dat...
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4th ieee International Conference on Smart Cloud (ieee SmartCloud) / 3rd ieee International symposium on reinforcement learning (ieee ISRL)
作者: Han, Shujun Li, Jun Ma, Yuxiang Dong, Qian Wu, Di Chinese Acad Sci Comp Network Informat Ctr Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Henan Univ Sch Comp & Informat Engn Kaifeng 475004 Peoples R China Henan Univ Henan Key Lab Big Data Anal & Proc Kaifeng 475004 Peoples R China Foshan Univ Sch Elect Informat Engn Foshan 528000 Peoples R China Peoples Bank China Chengdu Branch Chengdu 610041 Peoples R China
Network Function Virtualization (NFV) is a rapidly evolving network technology in recent years. The purpose of NFV is to use virtualization technology to softwareize network functions, and dynamically deploy virtual n... 详细信息
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A Combined Policy Gradient and Q-learning Method for Data-driven Optimal Control Problems  9
A Combined Policy Gradient and Q-learning Method for Data-dr...
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9th International Conference on Information Science and Technology (ICIST)
作者: Lin, Mingduo Liu, Derong Zhao, Bo Dai, Qionghai Dong, Yi Guangdong Univ Technol Sch Automat Guangzhou Peoples R China Beijing Normal Univ Sch Syst Sci Beijing Peoples R China Tsinghua Univ Dept Automat Beijing Peoples R China Beijing Inst Technol Sch Opt & Photon Beijing Peoples R China
This paper focuses on the data-driven controller design for optimal control problems of nonlinear nonaffine discrete-time systems. A novel policy gradient and Q-learning (PGQL) adaptive algorithm which learns the opti... 详细信息
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learning Without External Reward
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ieee COMPUTATIONAL INTELLIGENCE MAGAZINE 2018年 第3期13卷 48-54页
作者: He, Haibo Zhong, Xiangnan Univ Rhode Isl Dept Elect Comp & Biomed Engn Kingston RI 02881 USA Univ North Texas Dept Elect Engn Denton TX 76203 USA
In the traditional reinforcement learning paradigm, a reward signal is applied to define the goal of the task. Usually, the reward signal is a "hand-crafted" numerical value or a pre-defined function: it tel... 详细信息
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adaptive dynamic programming for Robust Regulation and Its Application to Power Systems
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ieee TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2018年 第7期65卷 5722-5732页
作者: Yang, Xiong He, Haibo Zhong, Xiangnan Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Univ Rhode Isl Dept Elect Comp & Biomed Engn Kingston RI 02881 USA Univ North Texas Dept Elect Engn Denton TX 76207 USA
This paper presents a novel robust regulation method for a class of continuous-time nonlinear systems subject to unmatched perturbations. To begin with, the robust regulation problem is transformed into an optimal reg... 详细信息
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2019 ieee 58th Conference on Decision and Control, CDC 2019
2019 IEEE 58th Conference on Decision and Control, CDC 2019
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58th ieee Conference on Decision and Control, CDC 2019
The proceedings contain 1192 papers. The topics discussed include: stochastic subgradient methods for dynamic programming in continuous state and action spaces;characterizing the interplay between information and stre...
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