8 citations · 25 across the 5 of their papers we have counts for
8 papers
Spatio-temporal Incentives Optimization for Ride-hailing Services with Offline Deep Reinforcement Learning
Yanqiu Wu, Qingyang Li, Zhiwei Qin
A fundamental question in any peer-to-peer ride-sharing system is how to, both effectively and efficiently, meet the request of passengers to balance the supply and demand in real…
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace
Soheil Sadeghi Eshkevari, Xiaocheng Tang, Zhiwei Qin +4
In this study, a real-time dispatching algorithm based on reinforcement learning is proposed and for the first time, is deployed in large scale. Current dispatching methods in ride…
Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms
Xiaocheng Tang, Fan Zhang, Zhiwei Qin +6
Large ride-hailing platforms, such as DiDi, Uber and Lyft, connect tens of thousands of vehicles in a city to millions of ride demands throughout the day, providing great promises…
Real-world Ride-hailing Vehicle Repositioning using Deep Reinforcement Learning
Yan Jiao, Xiaocheng Tang, Zhiwei Qin +4
We present a new practical framework based on deep reinforcement learning and decision-time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on-dem…
Bayesian Meta-reinforcement Learning for Traffic Signal Control
Yayi Zou, Zhiwei Qin
In recent years, there has been increasing amount of interest around meta reinforcement learning methods for traffic signal control, which have achieved better performance compared…
Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation
Mengyue Yang, Qingyang Li, Zhiwei Qin +1
Contextual multi-armed bandit (MAB) achieves cutting-edge performance on a variety of problems. When it comes to real-world scenarios such as recommendation system and online adver…