35 citations · 50 across the 6 of their papers we have counts for
7 papers
Taming Spontaneous Stop-and-Go Traffic Waves: A Bifurcation Perspective of A Dynamical Map
Suzhou Huang, Jian Hu
We consider a discrete-time dynamical system in a car-following context. The system was recently introduced to parsimoniously model human driving behavior based on utility maximiza…
Beyond Charging Anxiety: An Explainable Approach to Understanding User Preferences of EV Charging Stations Using Review Data
Zifei Wang, Emmanuel Abolarin, Kai Wu +5
Electric vehicles (EVs) charging infrastructure is directly related to the overall EV user experience and thus impacts the widespread adoption of EVs. Understanding key factors tha…
Aligning Language Models with Offline Learning from Human Feedback
Jian Hu, Li Tao, June Yang +1
Learning from human preferences is crucial for language models (LMs) to effectively cater to human needs and societal values. Previous research has made notable progress by leverag…
Multi-subgoal Robot Navigation in Crowds with History Information and Interactions
Xinyi Yu, Jianan Hu, Yuehai Fan +2
Robot navigation in dynamic environments shared with humans is an important but challenging task, which suffers from performance deterioration as the crowd grows. In this paper, mu…
Policy Regularization via Noisy Advantage Values for Cooperative Multi-agent Actor-Critic methods
Jian Hu, Siyue Hu, Shih-wei Liao
Recent works have applied the Proximal Policy Optimization (PPO) to the multi-agent cooperative tasks, such as Independent PPO (IPPO); and vanilla Multi-agent PPO (MAPPO) which has…
Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
Jian Hu, Siyang Jiang, Seth Austin Harding +2
Many complex multi-agent systems such as robot swarms control and autonomous vehicle coordination can be modeled as Multi-Agent Reinforcement Learning (MARL) tasks. QMIX, a widely…
QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning
Jian Hu, Seth Austin Harding, Haibin Wu +2
In Cooperative Multi-Agent Reinforcement Learning (MARL) and under the setting of Centralized Training with Decentralized Execution (CTDE), agents observe and interact with their e…