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This article addresses the security problem of tracking control for nonlinear multiagent systems against jamming attacks. It is assumed that the communication networks among agents are unreliable due to the existence of jamming attacks, and a Stackelberg game is introduced to depict the interaction process between multiagent systems and malicious jammer. First, the dynamic linearization model of the system is established by applying a pseudo-partial derivative method. Then, a novel model-free security adaptive control strategy is proposed, so that the multiagent systems can achieve bounded tracking control in the mathematical expectation sense in spite of jamming attacks. Furthermore, a fixed threshold event-triggered scheme is utilized to reduce communication cost. It is worth noting that the proposed methods only require the input and output information of the agents. Finally, the validity of the proposed methods is illustrated through two simulation examples.
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http://dx.doi.org/10.1109/TNNLS.2023.3279144 | DOI Listing |
IEEE Trans Cybern
September 2025
This article investigates the leader-following consensus of nonlinear TDMAS under impulsive control with simultaneous consideration of packet loss and parameter mismatch. Specifically, the inherent parameter mismatch between the leader's dynamics and followers' dynamics is explicitly addressed. To mitigate communication frequency, two novel impulsive control protocols are developed: 1) a pure impulsive scheme for theoretical analysis and 2) a limited impulsive strategy for practical implementation.
View Article and Find Full Text PDFmedRxiv
August 2025
The Windreich Department of Artificial Intelligence and Human Health, Mount Sinai Medical Center, NY, USA.
Background: AI agents built on large language models (LLMs) can plan tasks, use external tools, and coordinate with other agents. Unlike standard LLMs, agents can execute multi-step processes, access real-time clinical information, and integrate multiple data sources. There has been interest in using such agents for clinical and administrative tasks, however, there is limited knowledge on their performance and whether multi-agent systems function better than a single agent for healthcare tasks.
View Article and Find Full Text PDFPLoS One
September 2025
Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks, School of Information Engineering, Wuhan University of Technology, Wuhan, Hubei, China.
The H-beam riveting and welding work cell is an automated unit used for processing H-beams. By coordinating the gripping and welding robots, the work cell achieves processes such as riveting and welding stiffener plates, transforming the H-beam into a stiffened H-beam. In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells.
View Article and Find Full Text PDFFront Robot AI
August 2025
Information Technologies Institute, The Centre for Research and Technology Hellas, Thessaloniki, Greece.
Agentic AI refers to autonomous systems that can perceive their environment, make decisions, and take actions to achieve goals with minimal or no human intervention. Recent advances in Large Language Models (LLMs) have opened new pathways to imbue robots with such "agentic" behaviors by leveraging the LLMs' vast knowledge and reasoning capabilities for planning and control. This survey provides the first comprehensive exploration of LLM-based robotic systems integration into agentic behaviors that have been validated in real-world applications.
View Article and Find Full Text PDFPsychon Bull Rev
September 2025
Department of Psychology, Ariel University, Ariel, Israel.
How do people know when they are right? Confidence judgments - the ability to assess the correctness of one's own decisions - are a key aspect of human metacognition. This self-evaluative act plays a central role in learning, memory, consciousness, and group decision-making. In this paper, I reframe metacognition as a structured exchange of information between stimulus, decision-maker (the actor), and confidence judge (the rater), akin to a multi-agent communication system.
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