基于多智能体深度强化学习的智慧医疗网络计算卸载方法OA

The significant breakthroughs in 6G and mobile edge computing technologies have driven the flourishing development of smart healthcare services.In order to meet the requirements of low latency and high reliability in healthcare services,a computational offloading method based on multi-agent deep reinforcement learning is proposed.Considering the latency and energy consumption,a mixed integer nonlinear programming(MINLP)task offloading problem is formulated.The resource allocation problem is solved by a traditional optimization algorithm and the offloading decision problem is solved by a multi-agent deep reinforcement learning algorithm.Simulation results show that the proposed algorithm can perform real-time task offloading in dynamically changing environments of smart healthcare networks compared with several existing approaches.