报告主题：Statistical Inference in Reinforcement Learning

时间：2023年9月15日13:30-14:30

地点：上川路校区一教218

报告人：史成春

报告内容简介：

Reinforcement learning (RL) is concerned with how intelligence agents take actions in a given environment to maximize the cumulative reward they receive. In healthcare, applying RL algorithms could assist patients in improving their health status. In ride-sharing platforms, applying RL algorithms could increase drivers' income and customer satisfaction. RL has been arguably one of the most vibrant research frontiers in machine learning over the last few years. Nevertheless, statistics as a field, as opposed to computer science, has only recently begun to engage with reinforcement learning both in depth and in breadth. In today's talk, I will discuss some of my recent work on developing statistical inferential tools for reinforcement learning, with applications to mobile health and ridesharing companies. The talk will cover several different papers published in highly-ranked statistical journals (JASA & JRSSB) and top machine learning conferences (ICML).

主讲人简介：

史成春，伦敦政治经济学院的副教授，在Journal of the American Statistical Association等期刊发表论文数十篇，担任JRSSB、JASA（理论与方法）和《Journal of Nonparametric Statistics》等刊物副主编。研究重点是开发强化学习中的统计学习方法，并将其应用于医疗保健、共享汽车、视频共享和神经成像。他是2021年英国皇家统计学会研究奖的获得者，并连续三年获得IMS旅行奖。