Ieee-Caa Journal of Automatica Sinica最新文献_第2页

Multi-View Dynamic Kernelized Evidential Clustering 多视角动态核化证据聚类

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-11-20 DOI: 10.1109/JAS.2024.124608

Jinyi Xu;Zuowei Zhang;Ze Lin;Yixiang Chen;Weiping Ding

引用次数: 0

Robust Offline Actor-Critic with On-Policy Regularized Policy Evaluation 稳健的离线行为批判与政策正则化政策评估

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-11-20 DOI: 10.1109/JAS.2024.124494

Shuo Cao;Xuesong Wang;Yuhu Cheng

{"title":"Robust Offline Actor-Critic with On-Policy Regularized Policy Evaluation","authors":"Shuo Cao;Xuesong Wang;Yuhu Cheng","doi":"10.1109/JAS.2024.124494","DOIUrl":"https://doi.org/10.1109/JAS.2024.124494","url":null,"abstract":"To alleviate the extrapolation error and instability inherent in Q-function directly learned by off-policy Q-learning (QL-style) on static datasets, this article utilizes the on-policy state-action-reward-state-action (SARSA-style) to develop an offline reinforcement learning (RL) method termed robust offline Actor-Critic with on-policy regularized policy evaluation (OPRAC). With the help of SARSA-style bootstrap actions, a conservative on-policy Q-function and a penalty term for matching the on-policy and off-policy actions are jointly constructed to regularize the optimal Q-function of off-policy QL-style. This naturally equips the off-policy QL-style policy evaluation with the intrinsic pessimistic conservatism of on-policy SARSA-style, thus facilitating the acquisition of stable estimated Q-function. Even with limited data sampling errors, the convergence of Q-function learned by OPRAC and the controllability of bias upper bound between the learned Q-function and its true Q-value can be theoretically guaranteed. In addition, the sub-optimality of learned optimal policy merely stems from sampling errors. Experiments on the well-known D4RL Gym-MuJoCo benchmark demonstrate that OPRAC can rapidly learn robust and effective task-solving policies owing to the stable estimate of Q-value, outperforming state-of-the-art offline RLs by at least 15%.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 12","pages":"2497-2511"},"PeriodicalIF":15.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Securing the Future After PagerBombs: Lifecycle Protection of Smart Devices via Blockchain Intelligence 在 PagerBombs 之后保护未来：通过区块链智能保护智能设备的生命周期

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-11-20 DOI: 10.1109/JAS.2024.125031

Fei Lin;Qinghua Ni;Jing Yang;Juanjuan Li;Nan Zheng;Levente Kovács;Radu Prodan;Mariagrazia Dotoli;Qing-Long Han;Fei-Yue Wang

{"title":"Securing the Future After PagerBombs: Lifecycle Protection of Smart Devices via Blockchain Intelligence","authors":"Fei Lin;Qinghua Ni;Jing Yang;Juanjuan Li;Nan Zheng;Levente Kovács;Radu Prodan;Mariagrazia Dotoli;Qing-Long Han;Fei-Yue Wang","doi":"10.1109/JAS.2024.125031","DOIUrl":"https://doi.org/10.1109/JAS.2024.125031","url":null,"abstract":"The Lebanese wireless device explosion incident has drawn widespread attention, involving devices such as pagers, walkie-talkies, and other common devices [1]. This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment, signaling the onset of a new wave of “supply chain warfare” [2]. Even worse, with the rapid proliferation of Internet of Things (IoT) devices and smart hardware, the fragility of global supply chains would become increasingly fatal and significant, since almost all devices of daily usage could be maliciously programmed and triggered as weapons of massive destruction. Given this, we need new thinking and new approaches for improving supply chain security [3]. With its decentralized, tamper-proof, and highly traceable characteristics, blockchain technology is considered an effective solution to address these security threats [4], [5]. How to secure the entire lifecycle of smart devices, from production and transportation to usage, through blockchain-enabled safety management and protection, has become a pressing issue that requires immediate attention.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 12","pages":"2355-2358"},"PeriodicalIF":15.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linear Programming-Based Consensus of Positive Continuous-Time Multi-Agent Systems 基于线性规划的正向连续时间多代理系统共识

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-11-20 DOI: 10.1109/JAS.2024.124716

Junfeng Zhang;Fengyu Lin;Shihong Ding;Wei Xing

引用次数: 0

High-Order Fully Actuated System Models for Strict-Feedback Systems with Increasing Dimensions 尺寸不断增大的严格反馈系统的高阶全驱动系统模型

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-11-20 DOI: 10.1109/JAS.2024.124599

Xiang Xu;Guang-Ren Duan

引用次数: 0

A Double Sensitive Fault Detection Filter for Positive Markovian Jump Systems with A Hybrid Event-Triggered Mechanism 采用混合事件触发机制的正马尔可夫跃迁系统双敏故障检测滤波器

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-10-08 DOI: 10.1109/JAS.2024.124677

Junfeng Zhang;Baozhu Du;Suhuan Zhang;Shihong Ding

引用次数: 0

General Lyapunov Stability and its Application to Time-Varying Convex Optimization 一般李雅普诺夫稳定性及其在时变凸优化中的应用

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-10-08 DOI: 10.1109/JAS.2024.124374

Zhibao Song;Ping Li

{"title":"General Lyapunov Stability and its Application to Time-Varying Convex Optimization","authors":"Zhibao Song;Ping Li","doi":"10.1109/JAS.2024.124374","DOIUrl":"https://doi.org/10.1109/JAS.2024.124374","url":null,"abstract":"In this article, a general Lyapunov stability theory of nonlinear systems is put forward and it contains asymptotic/finite-time/fast finite-time/fixed-time stability. Especially, a more accurate estimate of the settling-time function is exhibited for fixed-time stability, and it is still extraneous to the initial conditions. This can be applied to obtain less conservative convergence time of the practical systems without the information of the initial conditions. As an application, the given fixed-time stability theorem is used to resolve time-varying (TV) convex optimization problem. By the Newton's method, two classes of new dynamical systems are constructed to guarantee that the solution of the dynamic system can track to the optimal trajectory of the unconstrained and equality constrained TV convex optimization problems in fixed time, respectively. Without the exact knowledge of the time derivative of the cost function gradient, a fixed-time dynamical non-smooth system is established to overcome the issue of robust TV convex optimization. Two examples are provided to illustrate the effectiveness of the proposed TV convex optimization algorithms. Subsequently, the fixed-time stability theory is extended to the theories of predefined-time/practical predefined-time stability whose bound of convergence time can be arbitrarily given in advance, without tuning the system parameters. Under which, TV convex optimization problem is solved. The previous two examples are used to demonstrate the validity of the predefined-time TV convex optimization algorithms.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 11","pages":"2316-2326"},"PeriodicalIF":15.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Transfer Learning Framework for Deep Multi-Agent Reinforcement Learning 深度多代理强化学习的迁移学习框架

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-10-08 DOI: 10.1109/JAS.2023.124173

Yi Liu;Xiang Wu;Yuming Bo;Jiacun Wang;Lifeng Ma

引用次数: 0

Prediction-Based State Estimation and Compensation Control for Networked Systems with Communication Constraints and DoS Attacks 具有通信限制和 DoS 攻击的网络系统的基于预测的状态估计和补偿控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-10-08 DOI: 10.1109/JAS.2024.124605

Zhong-Hua Pang;Qian Cao;Haibin Guo;Zhe Dong

引用次数: 0

Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning 通过相关扰动消除和纹理重构学习增强图像效果

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-10-08 DOI: 10.1109/JAS.2024.124521

Kui Jiang;Ruoxi Wang;Yi Xiao;Junjun Jiang;Xin Xu;Tao Lu

{"title":"Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning","authors":"Kui Jiang;Ruoxi Wang;Yi Xiao;Junjun Jiang;Xin Xu;Tao Lu","doi":"10.1109/JAS.2024.124521","DOIUrl":"https://doi.org/10.1109/JAS.2024.124521","url":null,"abstract":"Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network (PerTeRNet). It contains two sub-networks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery, we develop a novel perturbation-guided texture enhancement module (PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://github.com/kuijiang94/PerTeRNet.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 11","pages":"2253-2269"},"PeriodicalIF":15.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0