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IEEE TRANSACTIONS ON intelligent VEHICLES 2023年第4期8卷 2832-2841页

作者： Wang, Jiangong Wang, Xiao Tian, Yonglin Wang, Yutong Niu, Jinglong Kwan, Oliver Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Anhui Univ Sch Artificial Intelligence State Key Lab Management & Control Complex Syst Hefei 230031 Peoples R China Chinese Acad Sci Qingdao Acad Intelligent Ind State Key Lab Management & Control Complex Syst Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Acad Intelligent Ind Qingdao 266109 Peoples R China China North Ind North Automatic Control Technol Re Taiyuan 030006 Peoples R China Motion G Inc Singapore 068898 Singapore

The traffic environment and driving behaviors are of great complexity and uncertainty in our physical world. Therefore, training in the digital world with low cost and diverse complexities become popular for autonomous driving in recent years. However, the current training methods tend to be limited to static data sets and deterministic models that do not sufficiently take into account the uncertainty and diversity prevalent in real traffic scenarios. These approaches also limit more possibilities for the comprehensive development and optimization of vision systems. In this paper, we develop a parallel training method based on artificial systems, computational experiments, and parallel execution (ACP) for the intelligent optimization and learning of the aforementioned agents in uncertain driving spaces. Parallel training creates a virtual driving space following the instruction of the ACP approach and conducts large-scale rehearsal experiments for possible scenarios. By enhancing the diversity of virtual scenarios, intelligent vehicles are trained to respond and adapt to the diverse uncertainties in the physical real-world driving space. Specifically, parallel training first proposes a standard operating procedure for intelligent driving systems, namely the projection-emergence-convergence-operation (PECO) loop. Digital quadruplets for parallel training, i.e., physical, descriptive, predictive, and prescriptive coaches, are also proposed. With the guidance of parallel training, virtual and real-world driving spaces are set up in parallel and interact frequently. They are closely linked and unified in opposition to each other, ultimately building a parallel driving system that fulfills safety, security, sustainability, sensitivity, service, and smartness (6S).

关键词： Training Digital twins Testing Task analysis intelligent agents complex systems Uncertainty Parallel intelligence parallel driving digital quadruplets parallel learning digital twins metaverses automated driving knowledge transfer

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ACP theory based plant human machine interaction evaluation

ACP theory based plant human machine interaction evaluation

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Liu, Xiwei Shen, Xiaowei Fan, Dong State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457705731

It's an important need for a large chemical plant to roundly and deeply evaluate the design prototype of plant human machine interaction (HMI) using in the control room. To meet this need, we propose an evaluation method based on the ACP (Artificial system, Computational experiment, and Parallel execution) theory. A plant operator agent is created in the method and it is composed of perception, cognition, and execution processors, short-term memory, and long-term memory. The operator agent is used as a virtual subject, and the HMI can be evaluated by behavior simulation, from the viewpoints of shortening fault detection and isolation (FDI) track and decreasing operator's physical and mental workloads. The proposed method shows that the ACP theory is useful for the HMI evaluation. © 2011 IEEE.

关键词： Chemical plants

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A performance appraisal method based on ACP theory and PageRank algorithm

A performance appraisal method based on ACP theory and PageR...

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Shen, Xiaowei Liu, Xiwei Fan, Dong Cheng, Changjian Xiong, Gang State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781457705731

It is important for a chemical plant to find a suitable performance appraisal method. In this paper, based on the ACP (artificial system, computational experiment, and parallel execution) theory and the PageRank algorithm, a new performance appraisal method is proposed. The proposed method comprehensively involves both peoples and routine management rules from the holistic viewpoint. By comparison with the traditional performance appraisal method, the proposed method is more reasonable, more flexible and robuster. © 2011 IEEE.

关键词： Chemical plants

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Research on bus rapid transit (BRT) and its real-time scheduling

Research on bus rapid transit (BRT) and its real-time schedu...

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2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011

作者： Dong, Xisong Xiong, Gang Fan, Dong Zhu, Fenghua Lv, Yisheng State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Science Beijing China

ISBN: (纸本)9781457705731

With the fast development of the economy, the urban traffic demands increases rapidly, Bus rapid transit (BRT) system, a new type and high efficient bus operator system and a comprehensive mass transit system between the metro and regular bus systems, can alleviate traffic congestion, reduce resident traffic cost effectively, and improve transportation quality and efficiency, with its advantages becomes an effective way to improve urban traffic status. In this article, the definition, major elements, advantages, functions and development of BRT are provided, and a new real-time scheduling is given which is going to be applied to the Zhongshan Avenue BRT system in Guangzhou China. © 2011 IEEE.

关键词： Traffic congestion

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Leader-Following Consensus of Multi-Agent systems with Dynamic Leader and Measurement Noises 36

Leader-Following Consensus of Multi-Agent Systems with Dynam...

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第36届中国控制会议

作者： Yunpeng Wang Yunchun Xie Long Cheng Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781538629185

This paper studies a leader-following consensus problem of multi-agent systems with a dynamic *** is assumed that the leader moves along a polynomial trajectory with respect to time,while followers have first-order integral *** follower is equipped with the positioning system and ranger finder sensor to measure its own position and the relative positions with its *** measured information is corrupted by measurement *** first study a specials case of leader-following consensus problem（tracking problem）,then we extend the results to the general *** is assumed that leader’s velocity is unknown to all *** deal with this challenge,the least square is used to estimate leader’s *** on the estimated velocity and measured information,a consensus protocol is *** is proved that the proposed protocol can solve the mean square leader-following consensus problem under some mild *** simulation examples are also presented to demonstrate the effectiveness of the proposed protocol.

关键词： Leader-Following Consensus Mutli-Agent systems Dynamic Leader Measurement Noise Least Square Method

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Relaying Strategy Based on Estimated Information for Multi-Antenna Cooperative Networks

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China Communications 2017年第8期14卷 157-165页

作者： Shuangshuang Han Peng Zhang Feijin Shi Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of SciencesBeijingChina and Qingdao Academy of Intelligent Industries School of Computer Engineering Weifang University Communications Headquarters Ministry of Foreign Affairs of the People's Republic of China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina and Research Center of Computational Experiments and Parallel SystemsThe National University of Defense Technology

A sphere-based list forwarding scheme for multiple-input multiple-output(MIMO) relay networks is proposed and analyzed. Firstly, an estimate forwarding(EF) method is proposed, which forwards the minimum mean squared error(MMSE) estimate of the source data to the destination. Since it performs like amplify-and-forward(AF) and decode-and-forward(DF) for the low and high signal-to-noise ratio(SNR) regions, respectively, the EF relay thus outperforms conventional AF and DF across all SNRs without the need for switching algorithms for different SNRs. Because computational complexity is however high for relays with a large number of antennas(large MIMO) and/or high order constellations, list EF for large MIMO relay networks is proposed. It computes a list sphere decoder based MMSE estimate and retains the advantages of the exact EF relay at a negligible performance loss. The proposed list EF could offer a flexible trade-off between the performance and computational complexity.

关键词： MIMO system cooperative network soft information

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Budget allocation in competitive search advertisements

Budget allocation in competitive search advertisements

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21st Workshop on Information Technologies and systems, WITS 2011

作者： Yang, Yanwu Li, Juanjuan Zhang, Jie Zeng, Daniel State Key Lab. of Intelligent Control and Management of Complex Systems Chinese Academy of Sciences Beijing 100190 China Department of Management Information Systems University of Arizona United States

This paper proposes a novel budget model based on differential game to deal with budget allocation in competitive search advertisements under a finite time horizon, with consideration of budget constraints. We extend the advertising response function with the dynamical advertising effort u and quality score q to fit search advertising scenarios. We also discuss Nash equilibriums of our model, and study some desirable properties of two kinds of equilibriums in the case with budget constraints: "budget-stable" open-loop Nash equilibrium (BS-OLNE) and "budget-unstable" open-loop Nash equilibrium (BUS-OLNE). We have evaluated our budget model and identified properties with computational experiments. Experimental results show that budget strategies with dynamical advertising elasticity are superior to those with fixed one and our findings on OLNEs are helpful for advertisers to make budget decisions.

关键词： Marketing

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PDP: Parallel Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 1-5页

作者： Fei-Yue Wang Jie Zhang Qinglai Wei Xinhu Zheng Li Li IEEE State Key Laboratory of Management and Control for Complex Systems(SKL-MCCS) Institute of AutomationChinese Academy of Sciences(CASIA) School of Computer and Control Engineering University of Chinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Qingdao Academy of Intelligent Industries Department of Computer Science and Engineering University of Minnesota Department of Automation Tsinghua University

Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive dynamic programming ADP is first presented instead of direct dynamic programming DP , and the inherent relationship between ADP and deep reinforcement learning is developed. Next, analytics intelligence, as the necessary requirement, for the real reinforcement learning, is discussed. Finally, the principle of the parallel dynamic programming, which integrates dynamic programming and analytics intelligence, is presented as the future computational intelligence. © 2014 Chinese Association of Automation.

关键词： Artificial intelligence Neural networks Reinforcement learning

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Social Manufacturing for High-end Apparel Customization

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 489-500页

作者： Xiuqin Shang Fei-Yue Wang Gang Xiong Timo R. Nyberg Yong Yuan Sheng Liu Chao Guo Sen Bao State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Science at Aalto University Aalto FI-00076 Finland Qingdao Academy of Intelligent Industries Qingdao 266109 China IEEE

Social manufacturing(SM), a novel distributed,collaborative and intelligent manufacturing mode, is proposed and developed for high-end apparel customization. The main components of SM cloud are designed, and its research topics are summarized. Then, SM's key technologies are studied. 3D technologies for apparel customization, like 3D modeling, 3D fitting mirror and 3D customization, are developed to improve the customization precision and user experience. Information based collaborative management is realized to share, communicate,and handle the information efficiently among all groups and individuals of SM cloud. Suppliers' evaluation mechanism is designed to support the optimal decisions making. Next, SM cloud is constructed in five layers for high-end apparel *** using SM cloud based crowd-sourcing, social resources can be allocated rationally and utilized efficiently, consumer can customize the product in any processes like innovation, design,making, marketing and service, and traditional apparel enterprise can be upgraded into SM mode for keeping it competitive in the future customization markets.

关键词： Index Terms-Big data collaborative management social man-ufacturing cloud 3D apparel customization.

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Parallel Societies: A Computing Perspective of Social Digital Twins and Virtual-Real Interactions

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2020年第1期7卷 2-7页

作者： Wang, Fei-Yue Qin, Rui Li, Juanjuan Yuan, Yong Wang, Xiao Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

Welcome to the first issue of the IEEE Transactions on Computational Social systems (TCSS) of 2020, and Happy New Year to You! We would like to take this opportunity to express our sincere thanks to our editors, reviewers, authors, and readers for your great support and effort devoted to the TCSS, along with our best wish and hope that everyone has a happy, healthy, and fruitful 2020.

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