Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence

@article{Wei2022ReinforcementLM,
  title={Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence},
  author={Pengjin Wei and Kun Guo and Ye Li and Jue Wang and Wei Feng and Shi Jin and Ning Ge and Ying-Chang Liang},
  journal={IEEE Access},
  year={2022},
  volume={10},
  pages={65156-65192}
}
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its uncertainty, referred to as dynamic and randomness, from the mobile device, wireless channel, and edge network sides, results in high-dimensional, nonconvex, nonlinear, and NP-hard optimization problems. Thanks to the evolved reinforcement learning (RL), upon iteratively interacting with the dynamic and random environment, its… 
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