Sakana AI Unveils Multi-Agent Coordination Framework Sheaf-ADMM
SakanaAILabs · x · 2026-07-03
Sakana AI presents paper 'Learning Multi-Agent Coordination via Sheaf-ADMM', to be shown at ICML 2026. The framework addresses collective problem solving: splitting complex tasks into overlapping subtasks, each handled by an agent, solving global problems through negotiation, simulating swarm intelligence with individual limited perspectives.
Related event: Sakana AI Proposes Multi-Agent Coordination Framework Sheaf-ADMM(3 posts)→
More from Research
- Stanford Data-Centric AI Workshop reopens site, extends poster deadline — jure · 2026-10-26
- 'Vibe verification': ~60% of AI-written formal specs prove the wrong property — basedjensen · 2026-10-26
- Ito: a browser that detects browsing intent and auto-organizes tabs into Flows — andrewkuznet · 2026-10-26
- Cornell study says brains process language as linear sequences, challenging Chomsky's hierarchy — anirbanbandyo · 2026-10-26
- Hi3D V1.0 open-sourced with 2M training assets and 90% slicing success rate — kimmonismus · 2026-10-26
- Ortet evaluates 34 open-weight models on 50 health tasks, finds general leaderboards insufficient — elmanmansimov · 2026-10-26