Our paper, Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach, jointly written with Menna Hassan and Nourhan Sakr is now available on ArXiv. This paper designs a sequential repeated game of a micro-founded society with three types of agents: individuals, insurers, and a government. Nascent to economics literature, we use Reinforcement Learning (RL), closely related to multi-armed bandit problems, to learn the welfare impact of a set of proposed policy interventions per $1 spent on them. The paper rigorously discusses the desirability … <a …