Ivan Ilin, Peter Richtárik · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28286 · open-access PDF
ويستخدم فريقين من العاملين في نموذج اللغة الكبيرة (LLM) بشكل متزايد في المهام المعقدة، ولكن بروتوكولات التعاون الخاصة بهم تم تصميمها عادةً بشكل تجربي، دون ضمانات التفاوض. نحن نقوم بتصميم حل المشكلة التفاوضية كمتصفح تحسين: كل عامل يحسن جزءًا من الحل المشترك، وفقًا لمفهومه المحلي، بالإضافة إلى تصحيح كيف تؤثر التغييرات على أجزاء أخرى.
Machine translation (Meta M2M100); the English original follows.
Teams of large language model (LLM) agents are increasingly applied to complex tasks, but their collaboration protocols are mostly designed empirically, without convergence guarantees. We formalize collaborative problem solving as block optimization: each agent improves one part of a shared solution, guided by its local objective plus a correction for how its changes affect the other parts. A coordinator checks every proposal against the global objective and merges proposals that do not interfere with each other. We prove linear convergence up to an error floor that vanishes when the correctio
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