Publications
A collection of my research work.
Credit Assignment and Fine-Tuning Enhanced Reinforcement Learning for Collaborative Spatial Crowdsourcing
Wei Chen, Yafei Li, Baolong Mei, Guanglei Zhu, Jiaqi Wu, Mingliang Xu
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence 2025
We propose CAFE, a multi-agent RL framework for spatial crowdsourcing that addresses delayed rewards and non-stationary distributions through credit assignment mechanisms and adaptive fine-tuning, achieving superior task completion and equitable reward distribution.
Gradient-Guided Credit Assignment and Joint Optimization for Dependency-Aware Spatial Crowdsourcing
Yafei Li, Wei Chen, Jinxing Yan, Huiling Li, Lei Gao, Mingliang Xu
Proceedings of the AAAI Conference on Artificial Intelligence 2025
We propose RMO, a two-stage framework for dependency-aware spatial crowdsourcing that uses multi-agent RL for subtask recommendation and utility-based matching, employing meta-gradients and gradient synchronization to address credit assignment and joint optimization challenges.
Effective Task Assignment in Mobility Prediction-Aware Spatial Crowdsourcing
Huiling Li, Yafei Li, Wei Chen, Shuo He, Mingliang Xu, Jianliang Xu
2025 IEEE 41st International Conference on Data Engineering (ICDE) 2025
We address Task Assignment in Mobility Prediction-aware Spatial Crowdsourcing (TAMP) through a task-adaptive meta-learning algorithm that clusters workers and trains mobility prediction models, coupled with a task assignment algorithm that prioritizes high-confidence completions, achieving improved assignment quality.
Multi-aircraft cooperative decision-making methods driven by differentiated support demands for carrier-based aircraft
Wei Chen, Lulu Li, Dong Chen, Yafei Li, Ke Wang, Yuanyuan Jin, Mingliang Xu
ACTA AERONAUTICAET ASTRONAUTICA SINICA 2025
We propose DATSDM, a novel Dependency-Aware Task Scheduling Decision Module leveraging graph neural networks and Transformer attention mechanisms
Catcher: A Cache Analysis System for Top-k Pub/Sub Service
Baolong Mei, Yafei Li, Wei Chen, Linshen Luan, Guanglei Zhu, Yuanyuan Jin, Jianliang Xu
Proceedings of the VLDB Endowment 2024
We introduce Catcher, a multi-functional cache analysis system for Top-k Publish/Subscribe services that enable intuitive analysis of cache performance, bottleneck identification, and real-time evaluation through user-friendly interfaces.