An Explainable and Objective-Aware DRL Framework for MEC-Enabled Vehicular Networks
Multi-access Edge Computing (MEC) resource allocation in vehicular (V2X) networks is a multi-objective control problem that jointly optimizes latency, load balancing, and mobility constraints under highly dynamic conditions. Although deep reinforcement learning (DRL) can adapt to such environments, its decision-making...