7 citations · 9 across the 5 of their papers we have counts for
5 papers
Multi-Agent Path Finding with Prioritized Communication Learning
Wenhao Li, Hongjun Chen, Bo Jin +3
Multi-agent pathfinding (MAPF) has been widely used to solve large-scale real-world problems, e.g., automation warehouses. The learning-based, fully decentralized framework has bee…
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
Wenhao Li, Xiangfeng Wang, Bo Jin +3
When solving a complex task, humans will spontaneously form teams and to complete different parts of the whole task, respectively. Meanwhile, the cooperation between teammates will…
Learning Structured Communication for Multi-agent Reinforcement Learning
Junjie Sheng, Xiangfeng Wang, Bo Jin +5
This work explores the large-scale multi-agent communication mechanism under a multi-agent reinforcement learning (MARL) setting. We summarize the general categories of topology fo…
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning
Xuan Liao, Wenhao Li, Qisen Xu +5
Existing automatic 3D image segmentation methods usually fail to meet the clinic use. Many studies have explored an interactive strategy to improve the image segmentation performan…
Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning
Junjie Wang, Xiangfeng Wang, Bo Jin +3
Generalized zero-shot learning (GZSL) tackles the problem of learning to classify instances involving both seen classes and unseen ones. The key issue is how to effectively transfe…