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IEEE International Conference on systems, Man and Cybernetics

作者： Juanjuan Li Xiaolong Liang Rui Qin Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macau China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Decentralized Autonomous Organizations (DAOs) have been gaining popularity in recent years due to their promise of realizing the decentralized Web 3.0. However, most DAOs rely heavily on token-centric value systems as well as allocate decision-making authority and yield-sharing rights according to the held tokens, which often lead to monopolization of power and rights. To address this issue, this paper contributes to propose a truly democratic organization model, named True Autonomous Organizations and Operations (TAOs), that does not count upon tokens and is guided by principles of contribution-based and on-demand allocation. We first discuss the design of TAOs, including their infrastructures, power structures, and value systems, and then provide a technical roadmap for implementing TAOs in the DeSci context. This research can provide a valuable guidance for the construction and application of TAOs.

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management-Oriented Operating systems: Harnessing the Power of DAOs and Foundation Models

Management-Oriented Operating Systems: Harnessing the Power ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Rui Qin Juanjuan Li Xiaolong Liang Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macau China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This paper presents management-Oriented Operating systems (M2OS) that leverages the power of parallel intelligence theory, Decentralized Autonomous Organizations (DAOs) and foundation models to revolutionize the manner of management in Cyber-Physical-Social systems (CPSS). The parallel architecture on M2OS is proposed, including the parallel interactive actual M2OS and artificial M2OS. Among them, the artificial M2OSs provide digital infrastructures for organizations to operate, collaborate, and make decisions in the virtual space, and conduct computational experiments to evaluate management decisions and predict future states of the actual M2OS. Through parallel execution and closed-loop feedback between the artificial and actual M2OSs, the management and control, experimentation and evaluation, as well as learning and training of the actual M2OS can be realized. Moreover, the functional layers of M2OS, including the infrastructure layer, data layer, scenario layer, modeling layer, decision layer, and application layer, are discussed. These layers work together to support the intelligent, autonomous, collaborative, and adaptive nature of the M2OS, and facilitate data-driven decision-making, optimize business operations, and empower managers with real-time actionable insights. The proposed M2OS paradigm has great potential to transform the management paradigm and opens up new possibilities for intelligent and collaborative decision-making.

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Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence:mechanisms and applications of cognition,management,and control for complex systems

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Frontiers of Information Technology & Electronic Engineering 2022年第8期23卷 1142-1157页

作者： Fei-Yue WANG Jianbo GUO Guangquan BU Jun Jason ZHANG The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Grid Cooperation of China Beijing 100031China China Electric Power Research Institute Beijing 100192China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine *** need for using human-machine HAI in complex systems is then explained in *** concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid *** is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.

关键词： complex systems Human-machine knowledge automation Parallel systems Bulk power grid dispatch Artificial intelligence Internet of Minds(IoM)

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Towards Intelligent and Trustworthy Crowdsourcing systems with Cyber-physical Social Intelligence via Retrieval-augmented Generation

Towards Intelligent and Trustworthy Crowdsourcing Systems wi...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jing Yang Xingxia Wang Qinghua Ni Yuhang Liu Jing Wang Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350376739

ISBN: (纸本)9798350376746

In recent years, crowdsourcing systems that tackle complex tasks through the collective efforts of many individuals have garnered substantial attention. However, the existing crowd-sourcing systems face some challenges such as overreliance on human experience and effort, information overload, and risks of privacy breaches. To overcome these challenges, this paper proposes an intelligent and trustworthy crowdsourcing frame-work based on blockchain and retrieval-augmented generation. The framework centers around foundational models to integrate the three distinct and sequentially interdependent phases: task decomposition, task allocation or recommendation, and task execution, enabling the automatic provision of a personalized, comfortable, and efficient user experience. Blockchain and smart contracts are utilized to protect user privacy and interests without leaning on any third trusted authority. Additionally, the operational process of the framework is explained and validated by taking printed circuit board design and manufacturing as a case study and ChatGPT as its generator.

关键词： Crowdsourcing Retrieval augmented generation Smart contracts Privacy breach User experience Stability analysis Blockchains Social intelligence Resource management Reliability

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The Potential of Low-Altitude Airspace: The Future of Urban Air Transportation

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第8期9卷 5250-5254页

作者： Hailong Huang Jiangcheng Su Fei-Yue Wang Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic University Hong Kong China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Many megacities, such as London, New York, Paris, Tokyo, Beijing, and Shanghai, have been born due to urban- ization. While citizens enjoy the convenience of city life, such cities suffer from drawbacks of transportation: the average commute time has been increasing over the past years. With the maturity of electric vertical take-off and landing (eVTOL) aircraft technology, decision-makers have started to look upward to the low-altitude airspace. This blue space has the potential to reshape the transportation system and shorten the average travel time in daily life. To explore this emerging area, we held a Distributed/Decentralized Hybrid Workshop on Sustain- ability for Transportation and Logistics (DHW-STL), and this letter summarizes the outcomes of our discussion. Here, we first pinpoint the pain issues of conventional transportation. Then, we present the emerging low-altitude airspace transportation option, followed by a discussion on how such a new transportation option can integrate with the conventional ground-based transportation system. Some thoughts about the pathway to further development of the integrated transportation system are shared finally.

关键词： Aircraft Transportation Urban areas Air traffic control Traffic congestion Meters Aircraft propulsion Motors Logistics Indexes

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An-improved α-Shapes algorithm for solving collaborative workspaces of dual SCARA robots based on Monte Carlo method

An-improved α-Shapes algorithm for solving collaborative wo...

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第42届中国控制会议

作者： Feng-Yu Zhang Gang Yu Shu-Han He Wang-Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Huaxin Cement Technology Management (Wuhan) Co. Ltd.

Given the dual robots play a key role for collaborative work. In this paper, an improved method is proposed to find the kinematic positive solution based on its D-H parameters, model the dual SCARA robot in MATLAB environment, and solve the collaborative workspace point cloud map by Monte Carlo method. The proposed method extracts and plots the boundary curves of the collaboration space by improved the α-Shapes algorithm, and obtains the shape of the common region of the collaboration space of the dual SCARA robots and the limit position parameters in the collaboration space. It provides a theoretical basis for the research of path planning, trajectory planning, dynamics analysis, mechanism parameter optimization, self-avoidance, and anti-collision problems of the dual-robot collaborative system.

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Parallel control for Optimal Tracking via Adaptive Dynamic Programming

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IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1662-1674页

作者： Jingwei Lu Qinglai Wei Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078 Qingdao Academy of Intelligent Industries Qingdao 266109China

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback ***,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied *** address this problem,an augmented system and an augmented performance index function are proposed ***,the general nonlinear system is transformed into an affine nonlinear *** difference between the optimal parallel control and the optimal state feedback control is analyzed *** is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index ***,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function *** stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference ***,the effectiveness of the developed optimal parallel control method is verified in two cases.

关键词： Adaptive dynamic programming(ADP) nonlinear optimal control parallel controller parallel control theory parallel system tracking control neural network(NN)

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Moving Target Shooting control Policy Based on Deep Reinforcement Learning

Moving Target Shooting Control Policy Based on Deep Reinforc...

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2021 International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2021

作者： Li, Boyu Jin, Tao Zhu, Yuanheng Li, Haoran Wu, Yingnian Zhao, Dongbin Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Beijing Information Science and Technology University School of Automation Beijing100192 China

ISBN: (纸本)9781665402453

Robots are playing a more and more important role in people's production and life, recently. However, robot control in dynamic environment is still a difficulty. With the great breakthrough of deep reinforcement learning in the field of video games, this method is also extended to the field of robots. Due to the gap between the simulation environment and the real environment, the deep reinforcement learning algorithm trained in the simulation environment is difficult to be applied to the real environment. Aiming at the gimbal control with two degrees of freedom (DOF), a pipline combining system identification and deep reinforcement learning is proposed. On the one hand, the shooting accuracy of the gimbal to moving objects is improved through deep reinforcement learning algorithm. On the other hand, the gap between simulation and reality is reduced through system identification. The method is verified in the RoboMaster University AI Challenge (RMUA) shooting system. The results show that the shooting accuracy is better than the classical control method. © 2021 IEEE.

关键词： Deep learning

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Parallel vision and learning for intelligent perception in smart driving 1

Parallel vision and learning for intelligent perception in s...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Zhang, Hui Li, Yidong Li, Xuan Wang, Fei-Yue Beijing Jiaotong University Beijing China Peng Cheng Laboratory Shenzhen China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

Modern vision models are built upon large-scale diversified dataset, which is labor-intensive and cost-ineffective to collect and label. They are usually effective under simple constrained conditions, while the performance gets worse under actual traffic scenes. To address aforementioned problems, we propose a visual analysis framework based on parallel vision and learning for intelligent perception in smart driving. Specifically, our framework first generate and select data exploiting artificial image system. Then, computational experiments are conducted with predictive learning for model design, learning, and evaluation. Our framework is powered with virtual-actual interactive ability through parallel execution, integrating information from different scenes. The difficulty of the visual model in the actual scene can be applied to guide the model training in the artificial scene. We also carried out a case study to preliminarily demonstrate the effectiveness of the proposed framework. © 2021 IEEE.

关键词： Computer vision

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Stress Detection Using Wearable Devices based on Transfer Learning

Stress Detection Using Wearable Devices based on Transfer Le...

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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Wu, Jinting Zhang, Yujia Zhao, Xiaoguang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665401265

Excessive stress will have a negative impact on people's physical and mental health, especially for some special occupations. Because stressful stimuli can trigger a variety of physiological responses, analyzing physiological signals collected by wearable devices has become an important way to evaluate the stress state in recent years. However, the number of available subjects of a target group may be small, and collecting a large amount of data when the target group changes is costly and time-consuming. To solve this problem, we propose a stress detection framework for a small target group which uses adversarial transfer learning method to learn shared knowledge about stress between different groups. In order to verify the performance of the framework, we establish a dataset consisting of 264 ordinary college students and 32 police school students, aiming to evaluate the acute stress state of police school students under video stimuli for psychological training in the future. Comprehensive experiments show that our algorithm has achieved a significant improvement in the target group compared with the baseline methods. © 2021 IEEE.

关键词： Physiology

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