这篇论文提出了一个实用的容错框架DAS，专为工业场景下的异构智能体协作设计，解决了累积错误传播的老大难问题。
本文提出分布式智能体系统DAS，一种设备-边缘-云三层架构，用于异构智能体间的容错协作。系统定义智能体可靠性为系统级容错，而非单轮零错误准确率。架构包含两层：通过容错对齐实现单智能体执行可靠性，以及通过半形式化语言协议实现跨智能体通信可靠性。该框架为工业场景下异构具身智能体的可靠协作提供了工程路径。
Distributed Agent System: Fault-Tolerant Collaboration Among Embodied Agents
AI engineering is shifting from passive text generation by large language models (LLMs) to agent-driven task execution, creating new reliability challenges for long-horizon tasks under resource constraints and environmental uncertainty. Conventional error-elimination optimization strategies fail to address cumulative error propagation. This paper proposes Distributed Agent System (DAS), a device-edge-cloud framework for fault-tolerant collaboration among heterogeneous agents. We redefine agent reliability as system-level fault tolerance rather than single-turn zero-error accuracy, and present a two-layer fault-tolerance architecture: single-agent execution reliability via fault-tolerant alignment, and cross-agent communication reliability via semi-formal language protocols. This framework provides a practical engineering pathway for reliable heterogeneous embodied agents collaboration in industrial scenarios.