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ControlService: a containerized solution for control-algorithm-as-a-service in cloud control systems

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Science China(Information Sciences) 2024年第8期67卷 172-189页

作者： Chenggang SHAN Runze GAO Zhen YANG Wei ZHANG Yuanqing XIA School of Artificial intelligence Zaozhuang University School of Automation Beijing Institute of Technology

As an extension of networked control systems, cloud control systems(CCSs) have emerged as a new control paradigm to improve the service quality of emerging control missions, such as data-driven modeling and automated vehicles. Existing studies have used the workflow-based restructured method to optimize the computation-intensive algorithms in the CCSs. However, the challenges here are how to define and submit these algorithms' workflows as cloud services and execute these algorithms' workflows in a containerized manner. Based on these challenges, we propose a containerized solution for the control-algorithm-as-a-service(C3aS) in the CCSs, namely Control Service. It offers the control algorithm as a cloud workflow service and uses a customized workflow engine to realize the containerized execution. First, we employ a cloud workflow representation method to define a control algorithm into an abstract cloud workflow form. Afterward, we provide a cloud service representation of the abstract cloud workflow. Next, we design a workflow engine and submit the cloud service to this workflow engine to implement containerized execution of this cloud service in the CCSs. In the experiment, we discuss the cloud service form and containerized implementation of the subspace identification method. Experimental results show that the proposed Control Service has significant performance advantages in computational time, reduction percentage, and speedup ratio compared with the baseline method.

关键词： cloud control systems control-algorithm-as-a-service containerization workflow engine cloud workflow service subspace identification

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 37-57页

作者： Zhiqiang Pu Yi Pan Shijie Wang Boyin Liu Min Chen Hao Ma Yixiong Cui the School of Artificial intelligence University of Chinese Academy of Sciences the institute of Automation Chinese Academy of Sciences the Nanjing Artificial intelligence Research of IA the School of Sports Engineering Beijing Sport University

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) *** addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

关键词： Artificial intelligence(AI) decision-making football review soccer sports analytics

Emergence of machine language: towards symbolic intelligence with neural networks

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National Science Review 2024年第4期11卷 27-30页

作者： Yuqi Wang Xu-Yao Zhang Cheng-Lin Liu Tieniu Tan Zhaoxiang Zhang State Key Laboratory of Multimodal Artificial intelligence Systems Institute of AutomationChinese Academy of Sciences

Representation learning is a core issue in artificial intelligence (AI). Currently,there exists a disparity in the choice of representation between humans and machines. Humans rely on discrete language for communicati...

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Adaptive 5G-and-beyond network-enabled interpretable federated learning enhanced by neuroevolution

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Science China(Information Sciences) 2024年第7期67卷 107-132页

作者： Bin CAO Jianwei ZHAO Xin LIU Yun LI State Key Laboratory of Reliability and intelligence of Electrical Equipment Hebei University of Technology School of Artificial intelligence Hebei University of Technology School of Economics and Management Hebei University of Technology Industrial Artificial intelligence Centre Shenzhen Institute for Advanced StudyUniversity of Electronic Science and Technology of China

Mobile telemedicine systems based on the next-generation communication will significantly enhance deep fusion of network automation and federated learning(FL), but data privacy is a paramount issue in sectors like healthcare. This work hence considers FL augments 5G-and-beyond networks by training deep learning(DL) models without the need to exchange raw data. The substantial communication loads imposed on by extensive parameters involved in DL models are managed through adaptive scheduling mechanisms effectively. To address the opaque nature of DL models and to improve the interpretability of FL models, we introduce a convolutional fuzzy rough neural network specifically designed for medical image processing. We also develop a multiobjective memetic evolutionary algorithm to streamline and optimize the neural network architectures. Our comprehensive FL framework integrates smart scheduling, interpretable fuzzy rough logic,and neuroevolution. This framework is shown to improve communication efficiency, increase interpretability of diagnosis with protected privacy, and generate low-complexity neural architectures.

关键词： 5G-and-beyond network interpretable federated learning mobile telemedicine system fuzzy rough set theory neuroevolution

Key-Part Attention Retrieval for Robotic Object Recognition

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Tsinghua Science and Technology 2024年第3期29卷 644-655页

作者： Jierui Liu Zhiqiang Cao Yingbo Tang State KeyLaboratory of Multimodal Artificial intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial intelligence University of Chinese Academy of SciencesBeijing 100049China

The ability to recognize novel objects with a few visual samples is critical in the robotic *** methods mainly concern the recognition of inter-category objects,however,the object recognition fromdifferent sub-classes within the same category remains challenging due to their similar *** thispaper,we propose a key-part attention retrieval solution to distinguish novel objects of different sub-classesaccording to a few samples without ***,an object encoder,including convolutional neuralnetwork with attention and key-part aggregation,is designed to generate object attention map and extract theobject-level embedding,where object attention map from the middle stage of the backbone is used to guide thekey-part ***,to overcome the non-differentiability drawback of key-part attention,the objectencoder is trained in a two-step scheme,and a more stable object-level embedding is *** this basis,the potential objects are located from a scene image by mining connected domains of the attention *** the embedding of each potential object and embeddings from support data,the recognition of thepotential objects is *** effectiveness of the proposed method is verified by experiments.

关键词： key-part attention retrieval robotic object recognition

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu Hui Zeng Bin Fan the School of intelligence Science and Technology and the institute of Artificial intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

Gria:an efficient deterministic concurrency control protocol

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Frontiers of Computer Science 2024年第4期18卷 25-37页

作者： Xinyuan WANG Yun PENG Hejiao HUANG School of Computer Science and Technology Harbin Institute of TechnologyShenzhen 518055China institute of Artificial intelligence and Blockchain Guangzhou UniversityGuangzhou 510006China

Deterministic databases are able to reduce coordination costs in a *** property has fostered a significant interest in the design of efficient deterministic concurrency control ***,the state-of-the-art deterministic concurrency control protocol Aria has three ***,it is impractical to configure a suitable batch size when the read-write set is ***,Aria running in low-concurrency scenarios,e.g.,a single-thread scenario,suffers from the same conflicts as running in high-concurrency ***,the single-version schema brings write-after-write *** address these issues,we propose Gria,an efficient deterministic concurrency control *** has the following ***,the batch size of Gria is ***,Gria’s conflict probability in low-concurrency scenarios is lower than that in high-concurrency ***,Gria has no write-after-write conflicts by adopting a multi-version *** further reduce conflicts,we propose two optimizations:a reordering mechanism as well as a rechecking *** evaluation result on two popular benchmarks shows that Gria outperforms Aria by 13x.

关键词： deterministic concurrency control transaction processing

A Bio-Inspired Integration Model of Basal Ganglia and Cerebellum for Motion Learning of a Musculoskeletal Robot

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Journal of Systems Science & Complexity 2024年第1期37卷 82-113页

作者： ZHANG Jinhan CHEN Jiahao ZHONG Shanlin QIAO Hong State Key Laboratory of Multimodal Artificial intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial intelligence University of Chinese Academy of SciencesBeijing 100049China.

It is a significant research direction for highly complex musculoskeletal robots that how to develop the ability of motion learning and *** cooperations of multiple brain regions are crucial to improving motion *** by the neural mechanisms of structures,functions,and interconnections of basal ganglia and cerebellum,a biologically inspired integration model for motor learning of musculoskeletal robots is *** on the neural characteristics of the basal ganglia,the basal ganglia actor network,which mainly simulates the dorsal striatum,outputs motion commands,and the basal ganglia critic network,which simulates the ventral striatum,estimates actionstate *** network parameters are updated using the soft actor-critic *** on the sensorimotor prediction mechanism of the cerebellum,the cerebellum network evaluates the state feature extraction quality of the basal ganglia actor network and then updates the weights of its feature *** learning method is proven to converge to the optimal ***,drawing on the mechanism of dopaminergic dynamic regulation in the basal ganglia,the adaptive adjustment of target entropy and the dopaminergic experience replay are proposed to further improve the integration model,which contributes to the exploration-exploitation trade-off of motor *** bio-inspired integration model is validated on a musculoskeletal *** results indicate that this model can effectively control the musculoskeletal robot to accomplish the motion task from random starting locations to random target positions with high precision and robustness.

关键词： Basal ganglia and cerebellum bio-inspired integration model motion learning musculoskeletal robot reinforcement learning.

Non-Deterministic Liveness-Enforcing Supervisor Tolerant to Sensor-Reading Modification Attacks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 240-248页

作者： Dan You Shouguang Wang IEEE the School of Information and Electronic Engineering Sussex Artificial Intelligence InstituteZhejiang Gongshang UniversityHangzhou 310018China

In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.

关键词： Cyber-attacks cyber-physical system(CPS) liveness non-deterministic supervisors Petri net(PN)