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Adversary Detection and Resilient Control for Multi-Agent Systems
Then, based on the analysis and detection results, a resilient QP-based controller is presented to ensure safety and liveness constraints for intact agents.
Performance Analysis of Event-Triggered Consensus Control for Multi-agent Systems under Cyber-Physical Attacks
This work presents a rigorous analysis of the adverse effects of cyber-physical attacks on the performance of multi-agent consensus with event-triggered control protocols.
Assured Learning-enabled Autonomy: A Metacognitive Reinforcement Learning Framework
To guarantee performance while assuring satisfaction of safety constraints across variety of circumstances, an assured autonomous control framework is presented in this paper by empowering RL algorithms with metacognitive learning capabilities.
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