What is it about?
One of the machine learning methods that has been very popular among researchers in recent years is Reinforcement Learning (RL). Its most important advantage is the use of experiences gained from the environment for the agent. This is exactly the way a human learns. If we do something bad, we will be punished. In this way, we understand that we should not repeat that work in the future. Reinforcement learning is exactly that. In this systematic review, we address the most important RL research in edge/fog/cloud networks.
Featured Image
Photo by imgix on Unsplash
Why is it important?
RL is exactly the way that a human being learns based on the experiences gained from the environment. It is based on punishment/reward. This learning method has been proven to be more effective than supervised learning methods.
Perspectives
This article explains the previous studies of reinforcement learning in edge/fog/cloud networks in a very simple and understandable way. Especially students and young researchers can get a comprehensive view of the subject by reading this article.
Mohammad Hossein Rezvani
Qazvin Islamic Azad University
Read the Original
This page is a summary of: Reinforcement Learning Methods for Computing Offloading: A Systematic Review, ACM Computing Surveys, June 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3603703.
You can read the full text:
Resources
Contributors
The following have contributed to this page
