I am interested in adaptivity v.s. control in learning systems, knowledge representation and language systems. My PhD research is targeted at making Reinforcement Learning agents comply to regulations. Adaptivity can be of huge benefit in highly regulated domains such as healthcare and finance. In these domains, systems have to comply to regulations before they can be used. Understanding the regulations, on the other hand, is an expertise in itself. This project touches practical and fundamental aspects of explainability and safety of AI. How can we formalize regulations so that domain experts can inspect, understand and validate the result? How can we bridge the gap between experts' and RL agents' representation of the world and actions? How does constraining a RL agent impact its learning capabilities? In this project, we use an adaptive conversational agent for financial advice to investigate these issues.