試験JN0-251 トピック7 問題38 スレッド

In a Mist deployment, the Radio Resource Management (RRM) feature is an example of reinforcement learning. Reinforcement learning is a type of machine learning that works on the principle that an agent takes an action which is either penalized or rewarded based on the result in order to reinforce the optimal behavior1.
RRM is a feature that optimizes the wireless network performance and user experience by dynamically adjusting the radio frequency (RF) settings, such as channel, bandwidth, and power, of the access points (APs) based on the changing environmental conditions, such as interference, traffic, or user density2. RRM uses reinforcement learning to learn from the feedback and data collected by the APs and the Mist cloud and to make decisions that improve the network quality of service (QoS) and service level expectations (SLEs)3.