KAOS: Large Model Multi-Agent Operating System
Zhao Zhuo, Rongzhen Li, Kai Liu, Huhai Zou, KaiMao Li, Jie Yu, Tianhao, Sun, Qingbo Wu

TL;DR
KAOS introduces a multi-agent operating system leveraging large models to improve cross-platform user experience, resource sharing, and collaboration, validated through real application scenarios showing significant advantages.
Contribution
The paper presents KAOS, a novel multi-agent OS based on large models, with new management roles, collaboration strategies, and resource scheduling for improved multi-agent system performance.
Findings
Enhanced multi-agent collaboration efficiency
Improved resource utilization and scheduling
Validated system performance through real applications
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…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Multi-Agent Systems and Negotiation
