A hierarchical LLM-RL framework for joint UAV motion and connectivity optimization in HAPS-assisted networks achieves 14% better transportation efficiency, 25% higher throughput, and 23% fewer collisions in 3D simulations.
BDFL: A byzantine-fault-tolerance decentralized federated learning method for autonomous vehicle
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Hierarchical LLM-Driven Control for HAPS-Assisted UAV Networks: Joint Optimization of Flight and Connectivity
A hierarchical LLM-RL framework for joint UAV motion and connectivity optimization in HAPS-assisted networks achieves 14% better transportation efficiency, 25% higher throughput, and 23% fewer collisions in 3D simulations.