Optimizing Computation Offloading in IoV Environments: A Hybrid Learning Automata and Deep Recurrent Q-Network Approach
LA-DRQN is proposed, a novel hierarchical decision-making framework that synergistically integrates Learning Automata at the strategic level for macro-policy selection with a Deep Recurrent Q-Network (DRQN) at the tactical level for fine-tuning computation offloading ratios.