A deep reinforcement learning agent (MPDQN) selects RRI and transmission power in C-V2X Mode 4 to jointly minimize Age of Information and energy consumption, outperforming genetic and random baselines in simulation.
Anti-byzantine attacks enabled vehicle selection for asynchronous federated learning in vehicular edge computing,
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DRL-Based Optimization for AoI and Energy Consumption in C-V2X Enabled IoV
A deep reinforcement learning agent (MPDQN) selects RRI and transmission power in C-V2X Mode 4 to jointly minimize Age of Information and energy consumption, outperforming genetic and random baselines in simulation.