How can RL agents be monitored?
This is an open issue in Reinforcement Learning (and all of machine learning). Google has published a paper titled "Machine Learning: The High Interest Credit Card of Technical Debt" which addresses the many ways these systems can degrade over time.

One way is to follow fundamental production engineering techniques (e.g., test coverage and graceful exit). 

Another way is to monitor the data, then retrain the agent if new data is statistically out-of-sample.