10 papers
TAGA: Terrain-aware Active Gaze Learning for Generalizable Agile Humanoid Locomotion
Peizhuo Li, Hongyi Li, Mingfeng Fan +9
Agile humanoid locomotion across diverse challenging terrain demands both wide perceptual coverage and precise local geometry understanding. Motivated by the way humans selectively…
Learning to Solve Compositional Geometry Routing Problems
Mingfeng Fan, Jianan Zhou, Jiaqi Cheng +3
We study the Compositional Geometry Routing Problem (CGRP), a unified superclass of traditional routing problems that covers point-only, line-only, area-only, and arbitrary hybrid…
CROSS: A Mixture-of-Experts Reinforcement Learning Framework for Generalizable Large-Scale Traffic Signal Control
Xibei Chen, Yifeng Zhang, Yuxiang Xiao +3
Recent advances in robotics, automation, and artificial intelligence have enabled urban traffic systems to operate with increasing autonomy towards future smart cities, powered in…
LATS: Large Language Model Assisted Teacher-Student Framework for Multi-Agent Reinforcement Learning in Traffic Signal Control
Yifeng Zhang, Peizhuo Li, Tingguang Zhou +2
Adaptive Traffic Signal Control (ATSC) aims to optimize traffic flow and minimize delays by adjusting traffic lights in real time. Recent advances in Multi-agent Reinforcement Lear…
Unicorn: A Universal and Collaborative Reinforcement Learning Approach Towards Generalizable Network-Wide Traffic Signal Control
Yifeng Zhang, Yilin Liu, Ping Gong +3
Adaptive traffic signal control (ATSC) is crucial in reducing congestion, maximizing throughput, and improving mobility in rapidly growing urban areas. Recent advancements in param…
Preference-Driven Multi-Objective Combinatorial Optimization with Conditional Computation
Mingfeng Fan, Jianan Zhou, Yifeng Zhang +3
Recent deep reinforcement learning methods have achieved remarkable success in solving multi-objective combinatorial optimization problems (MOCOPs) by decomposing them into multipl…