One of the most common misconceptions about reinforcement learning (RL) applications is that, once you deploy them, they continue to learn. And, usually, I'm left having to explain this. As part of my explanations, I like to show where it is being used and where not.
I've done a little bit of research on the topic, but the descriptions seem fairly academic, and I'm left with the opinion that reinforcement learning is not really suitable for financial services in regulated markets.
Am I wrong? If so, I would like to know where RL is being used? Also, in those cases, are these RL algorithms adapting to new data over time? How do you ensure they are not picking up on data points or otherwise making decisions that are considered to be unacceptable?