Summary of Gonogo: An Efficient Llm-based Multi-agent System For Streamlining Automotive Software Release Decision-making, by Arsham Gholamzadeh Khoee et al.
GoNoGo: An Efficient LLM-based Multi-Agent System for Streamlining Automotive Software Release Decision-Making
by Arsham Gholamzadeh Khoee, Yinan Yu, Robert Feldt, Andris Freimanis, Patrick Andersson Rhodin, Dhasarathy Parthasarathy
First submitted to arxiv on: 19 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed GoNoGo system is a Large Language Model (LLM) agent designed to streamline automotive software deployment while meeting both functional requirements and practical industrial constraints. By leveraging zero-shot and few-shot examples taken from industrial practice, GoNoGo achieves a 100% success rate for tasks up to Level 2 difficulty with 3-shot examples. This efficient and user-friendly LLM-based solution automates decision-making for simpler tasks, significantly reducing the need for manual intervention. The system is specifically tailored to address domain-specific and risk-sensitive systems, making it an effective tool for assisting with software release decision-making in the automotive industry. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary GoNoGo is a special kind of computer program that helps make decisions about releasing new software in the car industry. Right now, people have to look at lots of data to decide if new software is ready to go out. This takes a long time and can be expensive. GoNoGo uses machines to help with this decision-making process. It’s really good at making simple decisions, but it also works well for more complicated tasks. The program helps reduce the need for humans to make decisions, which makes the whole process faster and cheaper. |
Keywords
» Artificial intelligence » Few shot » Large language model » Zero shot
