Dear Colleagues,
The Reinforcement Learning for Intelligent Transportation Systems Workshop (RL4ITS) will be held on Aug. 21, 2021 (Sat) in conjunction with the International Joint Conference on AI (IJCAI). Workshop website:
https://rl4its-ijcai21.github.io/workshopIntelligent transportation systems (ITS) are integrated systems that use advanced computer and communication technologies in road transportation, including vehicles, users, and infrastructure, and in traffic and mobility management, as well as for interfaces with other modes of transportation. There are challenging dynamic decision problems and critical questions that readily stand to benefit tremendously from AI.
Reinforcement learning for ITS is an emerging interdisciplinary area that is undergoing rapid development and still require further understanding on a number of issues, e.g., dynamic environments, run-time performance, and safe deployment. The main goal of this workshop is to bring together researchers and practitioners from both the RL and transportation communities to answer the following questions:
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What are the recent advances in the state-of-the-art of RL for ITS?
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What are the new application areas in transportation that can be benefited by RL?
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What are the successful stories in real-world applications of RL to ITS?
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What are the challenges and critical issues that may have significant impact on a successful application?
Answering these questions is critical to unleash the potential of the core intelligence in ITS beyond classical machine learning. We hope the participants will leave the workshop with a better idea about the current status of RL for ITS, about what is working well and what is not, thus providing guidance on directions of future research in this exciting area.
We have an impressive line-up of keynote speakers (in alphabetical order):
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Javier Alonso-Mora (Delft University of Technology)
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Alexandre Bayen (UC Berkeley)
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Jessie Li (Yunqi Academy of Engineering)
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Jun Luo (Huawei Noah's Ark Lab Canada)
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Pradeep Varakantham (Singapore Management University)
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Hai Yang (The Hong Kong University of Science and Technology)
There will also be three spotlight sessions showcasing the accepted papers of the workshop.
Detailed program schedule can be found at
https://rl4its-ijcai21.github.io/workshop . The workshop Zoom meeting can be accessed through the
IJCAI virtual conference platform (https://ijcai-21.org/ijcai-virtual-venue-access). Walk the avatar to meeting room Yellow 3 and press X upon entering.
This workshop is organized by Tony Qin, Liam Paull (U Montreal & MILA), Rui Song (NC State), and Hongtu Zhu (UNC Chapel Hill).
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Zhiwei (Tony) Qin
Principal Research Scientist | Director of AI Research
DiDi Labs
Mountain View, CA
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