题目：Reinforcement Learning

主讲人：伦敦政治经济学院 史成春副教授

主持人：西南财经大学统计学院 常晋源教授

时间：2024年11月4日（周一）上午09:00-12:00

    2024年11月5日（周二）下午09:00-12:00

    2024年11月6日（周三）上午09:00-12:00

地点：西南财经大学光华校区光华楼1003会议室

报告摘要：

Reinforcement learning (RL, see Sutton and Barto, 2018, for an overview) is a powerful machine learning technique that allows an agent to learn and interact with a given environment, to maximize the cumulative reward the agent receives. It has been one of the most popular research topics in the machine learning and computer science literature over the past few years. Significant progress has been made in solving challenging problems across various domains using RL, including games, recommender systems, finance, healthcare, robotics, transportation. This course covers basics of RL. It contains three lectures, including

1. Foundations of Reinforcement Learning

2. Planning and Learning

3. Q-Learning and Beyond

We will also provide code to implement various RL algorithms discussed in the lecture. The materials of this course is available on http://github.com/callmespring/RL-short-course.

主讲人简介：

Chengchun Shi is an Associate Professor at London School of Eco- nomics and Political Science. He is serving as the associate editors of JRSSB, JASA (TM), JASA (CS) and Journal of Nonparametric Statistics. His research focuses on developing statistical learning methods in reinforcement learning, with applications to healthcare, ridesharing, video-sharing and neuroimaging. He was the recipient of the Royal Statistical Society Research Prize in 2021 and IMS Tweedie Award in 2024