As large language model (LLM) agents increasingly integrate into our infrastructure, their robust coordination and message synchronization become vital. The Byzantine Generals Problem (BGP) is a critical model for constructing resilient multi-agent systems (MAS) under adversarial attacks. It describes a scenario where malicious agents with unknown identities exist in the system-situations that, in our context, could result from LLM agents' hallucinations or external attacks. In BGP, the objective of the entire system is to reach a consensus on the action to be taken. Traditional BGP requires global consensus among all agents; however, in practical scenarios, global consensus is not always necessary and can even be inefficient. Therefore, there is a pressing need to explore a refined version of BGP that aligns with the local coordination patterns observed in MAS. We refer to this refined version as Imperfect BGP (IBGP) in our research, aiming to address this discrepancy. To tackle this issue, we propose a framework that leverages consensus protocols within general MAS settings, providing provable resilience against communication attacks and adaptability to changing environments, as validated by empirical results. Additionally, we present a case study in a sensor network environment to illustrate the practical application of our protocol.

翻译：随着大型语言模型（LLM）智能体日益融入基础设施，其鲁棒的协调与消息同步变得至关重要。拜占庭将军问题（BGP）是构建对抗攻击下弹性多智能体系统（MAS）的关键模型。该模型描述了系统中存在身份未知的恶意智能体的场景——在我们的研究背景下，此类情形可能源于LLM智能体的幻觉或外部攻击。在BGP中，整个系统的目标是对待执行行动达成共识。传统BGP要求所有智能体达成全局共识；然而在实际场景中，全局共识并非总是必要，甚至可能导致效率低下。因此，迫切需要探索一种符合MAS局部协调模式的BGP改进版本。我们在研究中将这一改进版本称为非完美拜占庭将军问题（IBGP），旨在解决这一差异。为应对该问题，我们提出了一个在通用MAS设置中利用共识协议的框架，通过实证结果验证，该框架能够提供可证明的通信攻击抵御能力及对动态环境的适应性。此外，我们通过传感器网络环境中的案例研究展示了该协议的实际应用。