Dear colleagues, next Thursday, May 21 at 11:00 a.m. in Arzelà (5th floor, Department of Mathematics, Piazza di Porta San Donato, Bologna), there will be a seminar by Jodi Dianetti, University of Rome Tor Vergata, entitled: "REINFORCEMENT LEARNING FOR EXPLORATORY OPTIMAL STOPPING: A SINGULAR CONTROL FORMULATION" and abstract "In this talk we discuss continuous-time and state-space optimal stopping problems from a reinforcement learning perspective. We begin by formulating the stopping problem using randomized stopping times, where the decision maker's control is represented by the probability of stopping within a given time--specifically, a bounded, non-decreasing, càdlàg control process. To encourage exploration and facilitate learning, we introduce a regularized version of the problem by penalizing it with the cumulative residual entropy of the randomized stopping time. The regularized problem takes the form of an (n+1)-dimensional degenerate singular stochastic control with finite-fuel. We address this through the dynamic programming principle, which enables us to identify the unique optimal exploratory strategy. For the specific case of a real option problem, we derive a semi-explicit solution to the regularized problem, allowing us to assess the impact of entropy regularization and analyze the vanishing entropy limit. Finally, we propose a reinforcement learning algorithm based on policy iteration. We show policy improvement results for our proposed algorithm. This talk is based on a joint project together with Giorgio Ferrari and Renyuan Xu." It will be possible to follow online https://teams.microsoft.com/meet/363719926275962?p=aGps6f8abNyfzCedl5 https://teams.microsoft.com/meet/363719926275962?p=aGps6f8abNyfzCedl5 codice: ID riunione: 363 719 926 275 962 Passcode: yP9hT6CJ Best regards, Cristina Di Girolami