More agents don't help: a new survey gives three dimensions for scaling agent teams

人多不管用！智能体团队别盲目扩张，最新综述给出三大维度

Researchers from Emory University, the University of Oxford, and Griffith University propose a 3D framework for large-scale agent networks, classifying 8 system types by topology, memory scope, and update behavior. The survey says the core scaling bottleneck is not only communication protocols but inconsistent world models across agents; it also says current benchmarks stay small while real deployments may involve thousands to millions of agents.

Why it matters: Scores on all HKR axes: a contrarian hook, a concrete 3-axis/8-class framework, and strong resonance with agent-team builders. Kept at 78 because this is a review paper, not a model release or production deployment with fresh measured results.