2 citations · 3 across the 4 of their papers we have counts for
4 papers
Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning
Liu Weiwei, Hu Wenxuan, Jing Wei +3
Autonomous vehicles trained through Multi-Agent Reinforcement Learning (MARL) have shown impressive results in many driving scenarios. However, the performance of these trained pol…
The NEOLIX Open Dataset for Autonomous Driving
Lichao Wang, Lanxin Lei, Hongli Song +1
With the gradual maturity of 5G technology,autonomous driving technology has attracted moreand more attention among the research commu-nity. Autonomous driving vehicles rely on the…
Biased Estimates of Advantages over Path Ensembles
Lanxin Lei, Zhizhong Li, Dahua Lin
The estimation of advantage is crucial for a number of reinforcement learning algorithms, as it directly influences the choices of future paths. In this work, we propose a family o…
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning
Sirui Xie, Junning Huang, Lanxin Lei +4
Reinforcement learning agents need exploratory behaviors to escape from local optima. These behaviors may include both immediate dithering perturbation and temporally consistent ex…