RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning

Tong Wu, Jorge Ortiz

We introduce a new semi-supervised, time series anomaly detection algorithm that uses deep reinforcement learning (DRL) and active learning to efficiently learn and adapt to anomal…