Summary of Romas: a Role-based Multi-agent System For Database Monitoring and Planning, by Yi Huang et al.
ROMAS: A Role-Based Multi-Agent System for Database monitoring and Planning
by Yi Huang, Fangyin Cheng, Fan Zhou, Jiahui Li, Jian Gong, Hongjun Yang, Zhidong Fan, Caigao Jiang, Siqiao Xue, Faqiang Chen
First submitted to arxiv on: 18 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Databases (cs.DB); Multiagent Systems (cs.MA)
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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 Role-Based Multi-Agent System (ROMAS) is designed to adapt to various scenarios while enabling low code development and one-click deployment. ROMAS integrates role-based collaborative mechanisms for self-monitoring and self-planning, leveraging existing MAS capabilities to enhance database interactions. The system has been deployed in the DB-GPT project, showcasing its practical utility in real-world scenarios. Experimental evaluations demonstrate ROMAS’s superiority across multiple scenarios, highlighting its potential to advance multi-agent data analytics. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ROMAS is a new way for computers to work together and share tasks. It helps solve problems by letting different “roles” take over when needed, which makes it more efficient. This system has been tested in a real-world project called DB-GPT, which uses large language models to analyze data. The results show that ROMAS can do things better than other systems, making it important for advancing how computers work together. |
Keywords
» Artificial intelligence » Gpt
