KAOS: Large Model Multi-Agent Operating System

Authors: Zhao Zhuo, Rongzhen Li, Kai Liu, Huhai Zou, KaiMao Li, Jie Yu, Tianhao Sun, Qingbo Wu

The content is highly controversial and needs to be withdrawn

Results of the summarizing process for the arXiv paper: 2406.11342v3

  • Comprehensive Summary
  • Key points
  • Layman's Summary
  • Blog article
The summary is not ready yet

Abstract: The intelligent interaction model based on large models reduces the differences in user experience across various system platforms but faces challenges in multi-agent collaboration and resource sharing. To demonstrate a uniform user experience across different foundational software platforms and address resource coordination management challenges, this paper proposes KAOS, a multi-agent operating system based on the open-source Kylin. The research method involves empowering agents with large models to serve applications. First, by introducing management role agents and vertical multi-agent collaboration to construct or replace typical application software. Second, by studying system-level shared resource scheduling strategies to enhance user experience and optimize resource utilization. And finally, by validating the efficiency and superiority of the large model multi-agent operating system through real applications and scoring intelligence. The feasibility of this system is demonstrated, providing a new perspective for the development of multi-agent operating systems. Experimental results show significant advantages of multi-agent collaboration in various application scenarios.

Submitted to arXiv on 17 Jun. 2024

Tools for this paper

Explain it differently 3 free rewrites left today
Export BibTeX · RIS (Zotero, Mendeley, EndNote) · Markdown (Notion, Obsidian) · Premium
Citation alerts Premium
Journal club Slides to present it Premium
For journalists Press kit and hype check Premium

Ask questions about this paper to our AI assistant

You can also chat with multiple papers at once here.

⚠The license of the paper does not allow us to build upon its content and the AI assistant only knows about the paper metadata rather than the full article.

Figures and plots

Ask about a figure by number or use its question button to request visual analysis. Up to two figures and four image panels per question. Values read from plots are approximate; check the original data.

AI assistant instructions?

Assess the quality of the AI-generated content by voting

Score: 0

Why do we need votes?

Votes are used to determine whether we need to re-run our summarizing tools. If the count reaches -10, our tools can be restarted.

The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.

⚠The license of this specific paper does not allow us to build upon its content and the summarizing tools will be run using the paper metadata rather than the full article. However, it still does a good job, and you can also try our tools on papers with more open licenses.

Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.