462 citations · 1.9k across the 32 of their papers we have counts for
4 papers · 1 filter
Boosting Offline Reinforcement Learning with Residual Generative Modeling
Hua Wei, Deheng Ye, Zhao Liu +5
Offline reinforcement learning (RL) tries to learn the near-optimal policy with recorded offline experience without online exploration. Current offline RL research includes: 1) gen…
Learning to Route via Theory-Guided Residual Network
Chang Liu, Guanjie Zheng, Zhenhui Li
The heavy traffic and related issues have always been concerns for modern cities. With the help of deep learning and reinforcement learning, people have proposed various policies t…
Objective-aware Traffic Simulation via Inverse Reinforcement Learning
Guanjie Zheng, Hanyang Liu, Kai Xu +1
Traffic simulators act as an essential component in the operating and planning of transportation systems. Conventional traffic simulators usually employ a calibrated physical car-f…
Learning to Simulate on Sparse Trajectory Data
Hua Wei, Chacha Chen, Chang Liu +2
Simulation of the real-world traffic can be used to help validate the transportation policies. A good simulator means the simulated traffic is similar to real-world traffic, which…