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MAO: A Framework for Process Model Generation with Multi-Agent Orchestration by Lin, Leilei; Jin, Yumeng; Zhou, Yingming; Chen, Wenlong; Qian, Chen is a scholarly article available to read on EtoBox.

What is MAO: A Framework for Process Model Generation with Multi-Agent Orchestration about?

Process models are frequently used in software engineering to describe business requirements, guide software testing and control system improvement. However, traditional process modeling methods often require the participation of numerous experts, which is expensive and time-consuming. Therefore, the exploration of a more efficient and cost-effective automated modeling method has emerged as a focal point in current research. This article explores a framework for automatically generating process models with multi-agent orchestration (MAO), aiming to enhance the efficiency of process modeling and offer valuable insights for domain experts. Our framework MAO leverages large language models as the cornerstone for multi-agent, employing an innovative prompt strategy to ensure efficient collaboration among multi-agent. Specifically, 1) generation. The first phase of MAO is to generate a slightly rough process model from the text description; 2) refinement. The agents would continuously refine the initial process model through multiple rounds of dialogue; 3) reviewing. Large language models are prone to hallucination phenomena among multi-turn dialogues, so the agents need to review and r

Author

Lin, Leilei; Jin, Yumeng; Zhou, Yingming; Chen, Wenlong; Qian, Chen

Published

2024

Language

EN