Licheng Wang

MDGAM-Based Cooperative Task Scheduling for Communication-Constrained Distributed Multi-Agent Systems

A neural scheduling framework for distributed multi-robot task allocation, consisting of a multi-decoder graph attention model (MDGAM) policy model and a critic-free group relative multi-agent policy gradient (GRMAPG) training algorithm, which improves task-completion performance over existing heuristic and learning-based methods.