Bilevel Coordinated Reflection: A Game-Theoretic Approach to Multi-Agent LLM Systems
This paper develops a game-theoretic approach to multi-agent LLM systems, focusing on coordination, memory improvement, and external verification. Practitioners might care about this work because it provides a unified account of these aspects and introduces a new method, Stochastic Reflective Memory Ascent (SRMA), which can improve the performance of multi-agent LLM systems.