MULTI-AGENT REINFORCEMENT LEARNING FOR TASK OFFLOADING AND RESOURCE ALLOCATION IN MEC SYSTEMS
This paper addresses the joint task offloading and resource allocation problem in multi-user MEC systems and proposes a decentralized control framework based on Multi-Agent Reinforcement Learning (MARL), which achieves lower total system cost and faster convergence than the full-local, full-offload, and heuristic basel...