6 papers
Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments
Xin Ouyang, Songxin Lei, Xusen Guo +3
Using Unmanned Aerial Vehicle (UAV) for urban sensing has emerged as a powerful paradigm to monitor the status of the city, e.g., air quality and noise levels, through agile aerial…
Hierarchical Reinforcement Learning for Cooperative Air-Ground Delivery in Urban System
Songxin Lei, Chunming Ma, Haomin Wen +7
Cooperative air-ground delivery has emerged as a promising logistics paradigm by leveraging the complementary strengths of UAVs and ground carriers. However, effective dispatching…
A Game-Theoretic Spatio-Temporal Reinforcement Learning Framework for Collaborative Public Resource Allocation
Songxin Lei, Qiongyan Wang, Yanchen Zhu +6
Public resource allocation involves the efficient distribution of resources, including urban infrastructure, energy, and transportation, to effectively meet societal demands. Howev…
AgentSense: LLMs Empower Generalizable and Explainable Web-Based Participatory Urban Sensing
Xusen Guo, Mingxing Peng, Xixuan Hao +4
Web-based participatory urban sensing has emerged as a vital approach for modern urban management by leveraging mobile individuals as distributed sensors. However, existing urban s…
TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting
Jiaxi Hu, Qingsong Wen, Sijie Ruan +2
Recently, multivariate time series forecasting tasks have garnered increasing attention due to their significant practical applications, leading to the emergence of various deep fo…
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
Kang Luo, Yuanshao Zhu, Wei Chen +4
Trajectory modeling refers to characterizing human movement behavior, serving as a pivotal step in understanding mobility patterns. Nevertheless, existing studies typically ignore…