Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems
[Sztuczna inteligencja] Autorzy: Yihang Chen, Yuxiang Chen, Yuxuan Huang i 3 więcej
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-form reflection, we derive a finite-time upper bound, prove worst-case tightness, and give a positive lower bound under a falsifiable persistent-harm condition. We further prove an information-theoretic impossibility result: no gate that observes only the generated transcript can improve uniformly …
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja