6 citations · 12 across the 4 of their papers we have counts for
5 papers
Heterogeneous Policy Networks for Composite Robot Team Communication and Coordination
Esmaeil Seraj, Rohan Paleja, Luis Pimentel +7
High-performing human-human teams learn intelligent and efficient communication and coordination strategies to maximize their joint utility. These teams implicitly understand the d…
Step-by-Step Causality: Transparent Causal Discovery with Multi-Agent Tree-Query and Adversarial Confidence Estimation
Ziyi Ding, Chenfei Ye-Hao, Zheyuan Wang +1
Causal discovery aims to recover ``what causes what'', but classical constraint-based methods (e.g., PC, FCI) suffer from error propagation, and recent LLM-based causal oracles oft…
Learning Coordination Policies over Heterogeneous Graphs for Human-Robot Teams via Recurrent Neural Schedule Propagation
Batuhan Altundas, Zheyuan Wang, Joshua Bishop +1
As human-robot collaboration increases in the workforce, it becomes essential for human-robot teams to coordinate efficiently and intuitively. Traditional approaches for human-robo…
Heterogeneous Graph Attention Networks for Learning Diverse Communication
Esmaeil Seraj, Zheyuan Wang, Rohan Paleja +3
Multi-agent teaming achieves better performance when there is communication among participating agents allowing them to coordinate their actions for maximizing shared utility. Howe…
Learning to Dynamically Coordinate Multi-Robot Teams in Graph Attention Networks
Zheyuan Wang, Matthew Gombolay
Increasing interest in integrating advanced robotics within manufacturing has spurred a renewed concentration in developing real-time scheduling solutions to coordinate human-robot…