GoNoGo：一种基于LLM的高效多智能体系统，用于简化汽车软件发布决策
GoNoGo: An Efficient LLM-based Multi-Agent System for Streamlining Automotive Software Release Decision-Making
- Chalmers University of Technology（查尔姆斯理工大学）
- Volvo Group（沃尔沃集团）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出GoNoGo，一个面向汽车软件发布决策的LLM多智能体系统，通过少样本学习在简单任务上实现100%成功率，有效减少人工干预并支持风险敏感系统的及时决策。
AI中文摘要：
传统上，汽车行业中制定软件部署决策的方法通常依赖于对表格化软件测试数据的人工分析。由于劳动密集的特性，这些方法往往导致更高的成本和软件发布周期的延迟。大语言模型（LLMs）为这些挑战提供了一种有前景的解决方案。然而，它们的应用通常需要多轮人工驱动的提示工程，这限制了其实际部署，尤其是对于需要可靠且高效结果的工业终端用户而言。在本文中，我们提出了GoNoGo，这是一个LLM智能体系统，旨在简化汽车软件部署，同时满足功能需求和实际工业约束。与以往系统不同，GoNoGo专门针对领域特定和风险敏感的系统进行了定制。我们使用来自工业实践的零样本和少样本示例，在不同任务难度下评估了GoNoGo的性能。我们的结果表明，GoNoGo在使用3个示例时，对难度达到2级的任务实现了100%的成功率，并且即使在更复杂的任务上也保持了高性能。我们发现，GoNoGo有效地自动化了较简单任务的决策，显著减少了人工干预的需求。总之，GoNoGo代表了一种高效且用户友好的基于LLM的解决方案，目前已在我们的工业合作伙伴公司中使用，以协助软件发布决策，支持在风险敏感的车辆系统发布过程中做出更明智、更及时的决策。
英文摘要：
Traditional methods for making software deployment decisions in the automotive industry typically rely on manual analysis of tabular software test data. These methods often lead to higher costs and delays in the software release cycle due to their labor-intensive nature. Large Language Models (LLMs) present a promising solution to these challenges. However, their application generally demands multiple rounds of human-driven prompt engineering, which limits their practical deployment, particularly for industrial end-users who need reliable and efficient results. In this paper, we propose GoNoGo, an LLM agent system designed to streamline automotive software deployment while meeting both functional requirements and practical industrial constraints. Unlike previous systems, GoNoGo is specifically tailored to address domain-specific and risk-sensitive systems. We evaluate GoNoGo's performance across different task difficulties using zero-shot and few-shot examples taken from industrial practice. Our results show that GoNoGo achieves a 100% success rate for tasks up to Level 2 difficulty with 3-shot examples, and maintains high performance even for more complex tasks. We find that GoNoGo effectively automates decision-making for simpler tasks, significantly reducing the need for manual intervention. In summary, GoNoGo represents an efficient and user-friendly LLM-based solution currently employed in our industrial partner's company to assist with software release decision-making, supporting more informed and timely decisions in the release process for risk-sensitive vehicle systems.
