1 citations · 3 across the 6 of their papers we have counts for
7 papers
Bayesian Offline Multi-Agent Reinforcement Learning with Latent World Models
Xi Xiong, Lu Liu, Yiming Li +1
Model-based offline multi-agent reinforcement learning (MARL) provides a promising approach to multi-agent decision-making under partial observability, where the global state is un…
Offline Multi-Agent Reinforcement Learning with a Physics-Informed World Model for Cooperative Mixed Traffic Control
Lu Liu, Chi Xie, Xi Xiong
This study investigates cooperative control of connected and automated vehicles (CAVs) at partially observable highway bottlenecks in mixed traffic, aiming to mitigate congestion w…
SocialNav: Training Human-Inspired Foundation Model for Socially-Aware Embodied Navigation
Ziyi Chen, Yingnan Guo, Zedong Chu +14
Embodied navigation that adheres to social norms remains an open research challenge. Our SocialNav is a foundational model for socially-aware navigation with a hierarchical "brain-…
Optimizing Highway Traffic Flow in Mixed Autonomy: A Multiagent Truncated Rollout Approach
Lu Liu, Chi Xie, Xi Xiong
The development of connected and autonomous vehicles (CAVs) offers substantial opportunities to enhance traffic efficiency. However, in mixed autonomy environments where CAVs coexi…
Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic
Yuting Wang, Lu Liu, Maonan Wang +1
The burgeoning field of autonomous driving necessitates the seamless integration of autonomous vehicles (AVs) with human-driven vehicles, calling for more predictable AV behavior a…
A Multi-Agent Rollout Approach for Highway Bottleneck Decongestion in Mixed Autonomy
Lu Liu, Maonan Wang, Man-On Pun +1
The integration of autonomous vehicles (AVs) into the existing transportation infrastructure offers a promising solution to alleviate congestion and enhance mobility. This research…
Combining Policy Gradient and Safety-Based Control for Autonomous Driving
Xi Xiong, Lu Liu
With the advancement of data-driven techniques, addressing continuous con-trol challenges has become more efficient. However, the reliance of these methods on historical data intro…