We have the following seminar via google meet.

1.

Title: Introduction to Deep Q Learning and its application to finance
Time: November 23th (Monday) 09:30 – 10:10
Speaker: Prof. Chanho Min (Ajou University)
Abstract:
This seminar introduces the Deep Q Learning, one of the most popular methods of reinforcement learning and their application to finance problems. Reinforcement learning is a popular model of the learning problems through trial-and-error interactions in a certain given environment. This seminar will discuss the mathematical formulation of Deep Q learning and how each component plays a crucial role in agent learning. Finally it provides real world application in finance, and shows how reinforcement learning can outperform humans even with limited data.

2.

Title: Hamilton-Jacobi-Bellman equations for maximum entropy optimal control
Time: November 23th (Monday) 10:15 – 10:55
Speaker: Dr. Jeongho Kim (SNU)
Abstract:In this talk, we introduce an entropy-regularized optimal control problem for the deterministic control system. We derive dynamic programming principle and corresponding the Hamilton-Jacobi-Bellman (HJB) equation, which is regularized version of the HJB equation of the classical optimal control problem. After deriving the HJB equation, we provide several mathematical properties of it, including asymptotic convergence. We also provide an explicit example of control-affine problem, in which the optimal control is given as a normal distribution. Finally, we test the maximum entropy optimal control framework to several numerical examples, illustrating the benefit of the maximum entropy framework.