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It is proved that agents'parameters converge almost surely to the same limit points as in the attack-free case over time-varying communication graphs under linear parameterizations of the value and team-reward functions and Byzantine edge attacks.
DMBD enables multi-robot trajectory optimization in sub-seconds, dramatically enhancing scalability and coordination in complex environments.
Shifting from open-loop to closed-loop planning allows for more responsive and safer navigation in adversarial environments, significantly enhancing multi-objective kinodynamic planning.
Real-world cyber-physical system resilience demands a holistic approach integrating hardware, software, human factors, proactive measures, and adaptive recovery, moving beyond traditional fault models.
Achieve safety-critical control of adaptive systems without state derivative measurements by quantifying lumped disturbance and learning error with integral online conformal prediction.