Peer Selection Cuts Regret in Multi‑Agent Coordination
This story is from 2026-08-23. It is preserved in the archive; the latest stories are on the live feed.
Choosing complementary LLM partners slashes cumulative regret in cooperative tasks. The surprise is that the simplest stochastic policy—random pairing—outperforms sophisticated in‑context prompting when agents are left to wander alone. Before MACE, multi‑agent pipelines treated peer selection as an…
Read the full story at DEV Community — Machine Learning ↗
Timeline · 1 report
- 2026-08-23 05:00 · DEV Community — Machine Learning
Peer Selection Cuts Regret in Multi‑Agent Coordination