Dear all:
The Applied Reinforcement Learning (ARL) seminar is an online seminar that presents the latest advances in reinforcement learning applications and theory, organized by Drs. Rui Song, Hongtu Zhu, Tony Qin, Jieping Ye, and Michael R. Kosorok.
Reinforcement Learning (RL) learns how the agents should take actions when interacting with the environment to obtain the highest reward. Due to many successful applications in robotics, games, precision health, e-commerce, and ride-sharing industries, Reinforcemnt Learning (RL) has gained great popularity among various scientific fields. Our goal is to bring you a virtual seminar (approximately) featuring the latest work in applying reinforcement learning methods in many exciting areas (e.g., health sciences, ecommerce, medical imaging, and two-sided markets).
This time, the ARL Seminar is excited to welcome *Michael R. Kosorok* from the University of North Carolina at Chapel Hill who will take about "Off-policy Reinforcement Learning for Estimation of Optimal Treatment Regime"。 The seminar is on *Thursday， September 24th， 2020* at *8：00AM PT/10：00 AM CT/11：00 AM ET/4:00 PM London/11:00 PM Beijing*.
Details about the talk can be found on our website <https://arlseminar.com>.
If you are interested, you can register on our website<
https://www.arlseminar.com/registration-form/>. We will send the detailed information to your email address.
We look forward to seeing you on Thursday, Sept 24th.
Best
ARL Seminar.
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Hongtu Zhu
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