AINeutralarXiv – CS AI · May 276/10
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Intelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures
This academic survey examines deep reinforcement learning (DRL) approaches for optimizing computational offloading in vehicular edge computing systems. The research classifies existing DRL strategies across learning paradigms, system architectures, and optimization objectives while identifying challenges in scalability and coordination for next-generation intelligent transportation systems.