{"title":"DoS攻击下混合异构开放多智能体系统的自适应纳什均衡寻求","authors":"Shuting Chen;Ying Wan;Jinde Cao","doi":"10.1109/TNSE.2025.3553900","DOIUrl":null,"url":null,"abstract":"This paper investigates the problem of adaptive Nash equilibrium (NE) seeking in hybrid heterogeneous open multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. In the considered open MASs, agents can join or leave the network at any time, which leads to a changeable system size. To address this challenge, we propose a fully distributed control framework that enables agents with heterogeneous dynamics to converge to NE at an exponential rate, using only limited information exchange and localized computation. Additionally, an adaptive strategy is introduced, where the control gains of each agent are adjusted based on local adjacent information. This adjustment allows the system to adapt in real-time to environmental changes. We establish sufficient conditions for the existence of NE in both fixed and varying agent numbers, even in the presence of DoS attacks. Through rigorous theoretical analysis, the proposed adaptive algorithm is proven to guarantee the convergence of the hybrid heterogeneous MAS to the NE despite sustained or intermittent DoS attacks. Numerical simulations are provided to demonstrate the effectiveness of the proposed framework for open MASs in adversarial environments.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 4","pages":"2770-2782"},"PeriodicalIF":6.7000,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Nash Equilibrium Seeking in Hybrid Heterogeneous Open Multi-Agent Systems Under DoS Attacks\",\"authors\":\"Shuting Chen;Ying Wan;Jinde Cao\",\"doi\":\"10.1109/TNSE.2025.3553900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the problem of adaptive Nash equilibrium (NE) seeking in hybrid heterogeneous open multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. In the considered open MASs, agents can join or leave the network at any time, which leads to a changeable system size. To address this challenge, we propose a fully distributed control framework that enables agents with heterogeneous dynamics to converge to NE at an exponential rate, using only limited information exchange and localized computation. Additionally, an adaptive strategy is introduced, where the control gains of each agent are adjusted based on local adjacent information. This adjustment allows the system to adapt in real-time to environmental changes. We establish sufficient conditions for the existence of NE in both fixed and varying agent numbers, even in the presence of DoS attacks. Through rigorous theoretical analysis, the proposed adaptive algorithm is proven to guarantee the convergence of the hybrid heterogeneous MAS to the NE despite sustained or intermittent DoS attacks. Numerical simulations are provided to demonstrate the effectiveness of the proposed framework for open MASs in adversarial environments.\",\"PeriodicalId\":54229,\"journal\":{\"name\":\"IEEE Transactions on Network Science and Engineering\",\"volume\":\"12 4\",\"pages\":\"2770-2782\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-03-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Network Science and Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10937917/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10937917/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Adaptive Nash Equilibrium Seeking in Hybrid Heterogeneous Open Multi-Agent Systems Under DoS Attacks
This paper investigates the problem of adaptive Nash equilibrium (NE) seeking in hybrid heterogeneous open multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. In the considered open MASs, agents can join or leave the network at any time, which leads to a changeable system size. To address this challenge, we propose a fully distributed control framework that enables agents with heterogeneous dynamics to converge to NE at an exponential rate, using only limited information exchange and localized computation. Additionally, an adaptive strategy is introduced, where the control gains of each agent are adjusted based on local adjacent information. This adjustment allows the system to adapt in real-time to environmental changes. We establish sufficient conditions for the existence of NE in both fixed and varying agent numbers, even in the presence of DoS attacks. Through rigorous theoretical analysis, the proposed adaptive algorithm is proven to guarantee the convergence of the hybrid heterogeneous MAS to the NE despite sustained or intermittent DoS attacks. Numerical simulations are provided to demonstrate the effectiveness of the proposed framework for open MASs in adversarial environments.
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.