Ming-Qiang Li

SIGMA: Structured Noise-Effect-Aware Grouped Multi-Agent Aggregation

This work proposes SIGMA, a hierarchical collaboration framework that exploits cooperation structures to learn robust representations under noisy observations and demonstrates that SIGMA consistently improves robustness under observation noise while maintaining competitive performance in noise-free environments.