AI 中文总结
该研究指出基于LLM的多智能体系统的故障本质是并发控制问题，提出应将显式并发控制机制作为首要设计考量，以解决系统可靠性下降的问题。
AI 中文摘要
基于大语言模型（LLM）的多智能体系统（MAS）有望实现可扩展的协作，但增加智能体数量往往会降低可靠性。本立场论文指出，许多MAS故障本质上是并发控制问题：智能体并发读写共享状态，而LLM的长推理窗口会放大陈旧读取、丢失更新和结果不一致的风险。通常被归因于协调或通信故障的失效模式，可直接映射到经典并发异常。我们认为，MAS框架应通过显式并发控制机制解决这些故障：冲突检测、隔离保障以及对共享资源的结构化访问。并发控制应作为首要的设计考量，而非事后补充。
英文摘要
LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MAS failures are fundamentally concurrency control problems: agents concurrently read and write shared state, and long LLM inference windows amplify the risk of stale reads, lost updates, and inconsistent outcomes. Failure modes commonly attributed to coordination or communication breakdowns can be mapped directly onto classical concurrency anomalies. We contend that MAS frameworks should address these failures through explicit concurrency control mechanisms: conflict detection, isolation guarantees, and structured access to shared resources. Concurrency control should be a first-class design concern, not an afterthought.
Comments16 pages, 1 figure
