Can multi-agent LLMs improve engineering project solutions?
Harnessing Multi-Agent LLMs for Complex Engineering Problem-Solving: A Framework for Senior Design Projects
January 3, 2025
https://arxiv.org/pdf/2501.01205This research explores using a multi-agent system powered by LLMs (like GPT-4) to help engineering students with their complex capstone projects. The system acts like a virtual team of expert advisors, each focusing on a specific aspect of the project like problem formulation, ethical considerations, or technical feasibility.
Key points for LLM-based multi-agent systems:
- Role-Playing Agents: Each LLM agent is given a specific persona (e.g., "ethical advisor") to simulate a diverse team of experts.
- Centralized Coordination: A coordinator agent manages tasks and communication between the specialist agents.
- Iterative Feedback: Students receive feedback from the agents and can ask follow-up questions, promoting a dynamic learning process.
- Enhanced Learning: The system supports collaboration, critical thinking, and problem-solving skills development.
- Increased Accuracy: Multi-agent systems demonstrated better alignment with faculty evaluations compared to single LLM systems. They provide richer feedback, higher clause density and thematic unity in responses, and readability levels suitable for senior students.
- Open-Source Framework: The researchers have made their framework open source to encourage further development and adaptation for various educational contexts.