SOURCE-LINKED INTELLIGENCE

Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Multi-agent LLM systems commonly use an orchestrator to decompose a task for a team of workers and then improve through textual reflection. Despite strong empirical results, these systems lack a unified account of coordination, memory improvement, and the role of external verification. We model orchestrator-worker interaction as a bilevel coordination game: under bounded coupling, the workers' local-update game is an approximate potential game whose equilibrium slack is controlled by decomposition quality. We then analyse reflection as stochastic movement over semantic memory states. For free-

Read original source ↗ Open in workspace

recordType

paper

region

Global