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2024 China Automation Congress, CAC 2024

作者： Fang, Qihang Xiong, Gang Wang, Fang Shen, Zhen Dong, Xisong Wang, Fei-Yue State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350368604

Additive manufacturing (AM) is a promising technology to tailor complex structures in a layer-by-layer fashion. Its wide adoption, however, is hampered by occurrence of defects that deteriorates product quality. Defect detection methods have therefore been developed to address quality issues, primarily utilizing deep learning models. Despite achieving appreciable results, these models require a substantial amount of labeled data and extensive training, which are costly and time-consuming. Thus, it is worth developing a new approach that can perform defect detection (1) with minimal labeled data, and (2) without the necessity for model updating. Recently, the large language model (LLM) has demonstrated remarkable generalization capability across various fields. It features an in-context learning (ICL) capability that allows it to learn from a context without any retraining. This study explores the potential of applying an LLM for AM defect detection based on ICL. To this end, a dataset pertaining to the resin deposition status in vat photopolymerization, as a field where prevailing LLMs have limited exposure, is collected. Two contributions are made to achieve more accurate defect detection by prompting. First, a multimodal context that includes both image-label pairs and expert knowledge is tailored, which contains comprehensive information about deposition status. Second, a repeated query and voting (RQV) technique is proposed to mitigate occasional misjudgements, thus enhancing the reliability of the defect detection. Comprehensive ablation studies verify the effectiveness of both the multimodal context and RQV technique. As a result, 96.2% classification accuracy is achieved in such a challenging few-shot setting, obviating the need of model updating. © 2024 IEEE.

关键词： Labeled data

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Highway Lane Change Decision-Making via Attention-Based Deep Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 567-569页

作者： Junjie Wang Qichao Zhang Dongbin Zhao State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China IEEE

Dear editor,Deep reinforcement learning(DRL),combining the perception capability of deep learning(DL)and the decision-making capability of reinforcement learning(RL)[1],has been widely investigated for autonomous driving decision-making *** this letter,Fund:supported in part by the National Natural Science Foundation of China(NSFC)(62173325);the Beijing Municipal Natural Science Foundation(L191002).

关键词： driving Deep has

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Parallel Learning:Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 603-631页

作者： Qinghai Miao Yisheng Lv Min Huang Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Artificial Intelligence Anhui UniversityHefei 266114China Qingdao Academy of Intelligent Industries Qingdao 230031China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine *** summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel ***,an extended parallel learning framework is proposed to cover main domains including computer vision,natural language processing,robotics,and autonomous ***,a multi-dimensional taxonomy is designed to organize the literature in a hierarchical ***,the related virtual-toreal works are analyzed and compared according to the three principles of parallel learning known as description,prediction,and prescription,which cover the methods for constructing virtual worlds,generating labeled data,domain transferring,model training and testing,as well as optimizing the strategies to guide the task-oriented data generator for better learning *** issues remained in virtual-to-real are ***,the future research directions from the viewpoint of parallel learning are suggested.

关键词： Machine learning parallel learning parallel systems sim-to-real syn-to-real virtual-to-real

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Computational Experiments for complex Social systems:Experiment Design and Generative Explanation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1022-1038页

作者： Xiao Xue Deyu Zhou Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang the School of Computer Software College of Intelligence and ComputingTianjin UniversityTianjin 300350China the School of Software and the Joint SDUNTU Centre for Artificial Intelligence Research(C-FAIR) Shandong UniversityJinan 250101China the Information School Xi’an University of Financial and EconomicsXi’an 710100China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Hainan University Haikou 570228China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 1001901China

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system *** address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating ***,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

关键词： Agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model

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A DAOs-Based Publishing System for Advancing Open Access 4

A DAOs-Based Publishing System for Advancing Open Access

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Ma, Siji Li, Juanjuan Guan, Sangtian Ni, Qinghua Lin, Fei Zhang, Tengchao Huang, Jun Wang, Fei-Yue Macau University of Science and Technology Faculty of Innovation Engineering 999078 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

The development of the scientific publishing system has remarkably enhanced global accessibility to research findings and substantially increased the visibility and dissemination of academic publications. However, significant challenges still exist in effectively safeguarding the intellectual property rights of contributors, such as the unauthorized usage of materials, the complexity of enforcing intellectual property rights across various legal jurisdictions, and high instances of plagiarism and content misuse. Additionally, financial barriers related to open access may restrict the participation of economically disadvantaged researchers, potentially biasing scientific records towards more affluent research initiatives. To address these issues, a novel decentralized framework is formulated to ensure truly open access. This framework leverages blockchain for immutable record-keeping and clear attribution of authorship, to prevent unauthorized usage and plagiarism. Besides, it also utilizes a copyright-sharing model based on decentralized autonomous organizations and operations (DAOs), where smart contracts automatically enforce copyright and access policies to ensure fair compensation for authors and researchers. Furthermore, the copyright sharing model based on non-fungible tokens (NFT) and gradual ownership optimization (GOO) mechanism is proposed to ensure fair and accurate recognition and compensation for scholarly contributions. © 2024 IEEE.

关键词： Decentralized finance

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What Does ChatGPT Say:The DAO from Algorithmic Intelligence to Linguistic Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 575-579页

作者： Fei-Yue Wang Qinghai Miao Xuan Li Xingxia Wang Yilun Lin School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China Urban Computing Lab Department of Applied ResearchShanghai AI LaboratoryShanghai 200232China IEEE

THE well-known ancient Chinese philosopher Lao Tzu(老子)or Laozi(6th~4th century BC during the Spring and Autumn period)started his classic Tao Teh Ching《道德经》or Dao De Jing(see Fig.1)with six Chinese characters:"道(Dao)可(Ke)道(Dao)非(Fei)常(Chang)道(Dao)",which has been traditionally interpreted as“道可道,非常道”or"The Dao that can be spoken is not the eternal Dao".

关键词： DAO Intelligence Spring

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Chat with ChatGPT on Industry 5.0:Learning and Decision-Making for Intelligent Industries

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 831-834页

作者： Fei-Yue Wang Jing Yang Xingxia Wang Juanjuan Li Qing-Long Han State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia

THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algorithmic Intelligence to Linguistic Intelligence where interactive activities between actual and artificial,real and virtual,human and machine play an active and important role online and in *** IEEE/CAA JAS,we are interested in investigating the impact and significance of this new era on industrial development,especially control and automation for manufacturing and production.

关键词： GPT artificial automation

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A Novel Iterative Adaptive Critic Design for Smart Home Energy systems with Solar Energy

A Novel Iterative Adaptive Critic Design for Smart Home Ener...

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2022 Chinese Automation Congress, CAC 2022

作者： Liao, Zehua Wei, Qinglai Li, Hongyang University of Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems School of Artificial Intelligence Beijing China

ISBN: (纸本)9781665465335

As a distributed energy storage system, smart home energy (SHE) system can be used to reduce the consumption cost of household users. Aiming at the optimal control SHE systems, a novel multi-iteration adaptive dynamic programming (MIADP) method is constructed. The present algorithm introduces three iterations, namely, exterior iteration, local iteration and interior iteration, to ensure that the iterative Q-function converges to the optimal, and thus the optimal energy storage control scheme of the SHE system with solar energy is obtained. Finally, the present MIADP algorithm is illustrated by the experimental results. © 2022 IEEE.

关键词： Solar energy

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Evolution of Opinions with Estimation and Interference 41

Evolution of Opinions with Estimation and Interference

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第41届中国控制会议

作者： Yifa Liu Long Cheng State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The evolution of opinion is largely influenced by individual subjectivity,however,this is neglected in many studies about opinion *** paper analyzes the evolution of self-cognition and its impact on the spread of opinion from the perspective of individual ***,this paper considers the effect of external interference on the cluster by altering social interaction,and discusses the impact of demagoguery on individual self-cognition bias and polarization of the cluster.

关键词： Opinion dynamics Self-cognition Estimation

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Parallel Manufacturing for Industrial Metaverses:A New Paradigm in Smart Manufacturing

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IEEE/CAA Journal of Automatica Sinica 2022年第12期9卷 2063-2070页

作者： Jing Yang Xiaoxing Wang Yandong Zhao The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing SANBODY Technology Company LtdBeijing 214000China North Automatic Control Technology Institute Taiyuan 030006China

To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social systems(CPSSs) and the Internet of Minds(Io M) are regarded as its infrastructures and the "Artificial systems", "Computational experiments"and "Parallel execution"(ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R&D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation(KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations(DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case,especially the unmanned production line named Flex Vega.

关键词： Parallel Manufacturing Digital Workers CPSS Smart Manufacturing Industrial Metaverses

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