Dear Colleague,
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, Reinforcement Learning (RL) has gained great popularity among various scientific fields. The goal of the ARL Seminar 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, or two-sided markets).
This time, the ARL Seminar is excited to welcome *Tony Qin* from DiDi AI Labs who will talk about "Deep Reinforcement Learning in a Ride-sharing Marketplace". Tony Qin is Principal Research Scientist and Director of the reinforcement learning group at DiDi AI Labs, working on core problems in ridesharing marketplace optimization. Prior to DiDi, Tony Qin was a research scientist in supply chain and inventory optimization at Walmart Global E-commerce. His research interests span optimization and machine learning, with a particular focus in reinforcement learning and its applications in operational optimization, digital marketing, and smart transportation. He has published and served a program committee member in numerous top-tier conferences and journals in machine learning and optimization. He and his team received the INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice in 2019 and were selected for the NeurIPS 2018 Best Demo Awards. Tony holds more than 10 US patents in intelligent transportation and E-commerce systems.
The seminar is on *Wednesday, October 7th, 2020* at *8:00 AM 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 Wednesday, Oct 7th..
Best,
ARL Seminar
*Title: Deep Reinforcement Learning in a Ride-sharing Marketplace
*Abstract: With the rising prevalence of smart mobile phones in our daily life, online ride-hailing platforms have emerged as a viable solution to provide more timely and personalized transportation service, led by such companies as DiDi, Uber, and Lyft. These platforms also allow idle vehicle vacancy to be more effectively utilized to meet the growing need of on-demand transportation, by connecting potential mobility requests to eligible drivers. In this talk, we will describe our train of research on ride-hailing marketplace optimization at DiDi, in particular, order dispatching and vehicle repositioning. We will show the development of the spatiotemporal contextual value network and how it is used in order dispatching policy generation and decision-time planning in vehicle repositioning.
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Zhiwei Qin
Principal Research Scientist, Director of AI Research
DiDi Research America, LLC
Mountain View CA
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