Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web
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arXiv
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| Format: | Preprint |
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2026
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| author | Nie, Xiaohang Guo, Zihan Cui, Zicai Yang, Jiachi Chen, Zeyi De, Leheyi Zhang, Yu Liao, Junwei Huang, Bo Yang, Yingxuan Han, Zhi Peng, Zimian Chen, Linyao Tang, Wenzheng Tom Liu, Zongkai Zhou, Tao Hu, Botao Amber Tang, Shuyang Lin, Jianghao Liu, Weiwen Wen, Muning Zhou, Yuanjian Zhang, Weinan |
| author_facet | Nie, Xiaohang Guo, Zihan Cui, Zicai Yang, Jiachi Chen, Zeyi De, Leheyi Zhang, Yu Liao, Junwei Huang, Bo Yang, Yingxuan Han, Zhi Peng, Zimian Chen, Linyao Tang, Wenzheng Tom Liu, Zongkai Zhou, Tao Hu, Botao Amber Tang, Shuyang Lin, Jianghao Liu, Weiwen Wen, Muning Zhou, Yuanjian Zhang, Weinan |
| contents | As large language models (LLM)-driven agents transition from isolated task solvers to persistent digital entities, the emergence of the Agentic Web, an ecosystem where heterogeneous agents autonomously interact and co-evolve, marks a pivotal shift toward Artificial General Intelligence (AGI). However, LLM-based multi-agent systems (LaMAS) are hindered by open-world issues such as scaling friction, coordination breakdown, and value dissipation. To address these challenges, we introduce Holos, a web-scale LaMAS architected for long-term ecological persistence. Holos adopts a five-layer architecture, with core modules primarily featuring the Nuwa engine for high-efficiency agent generation and hosting, a market-driven Orchestrator for resilient coordination, and an endogenous value cycle to achieve incentive compatibility. By bridging the gap between micro-level collaboration and macro-scale emergence, Holos hopes to lay the foundation for the next generation of the self-organizing and continuously evolving Agentic Web. We have publicly released Holos (accessible at https://holosai.io), providing a resource for the community and a testbed for future research in large-scale agentic ecosystems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_02334 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web Nie, Xiaohang Guo, Zihan Cui, Zicai Yang, Jiachi Chen, Zeyi De, Leheyi Zhang, Yu Liao, Junwei Huang, Bo Yang, Yingxuan Han, Zhi Peng, Zimian Chen, Linyao Tang, Wenzheng Tom Liu, Zongkai Zhou, Tao Hu, Botao Amber Tang, Shuyang Lin, Jianghao Liu, Weiwen Wen, Muning Zhou, Yuanjian Zhang, Weinan Artificial Intelligence Multiagent Systems As large language models (LLM)-driven agents transition from isolated task solvers to persistent digital entities, the emergence of the Agentic Web, an ecosystem where heterogeneous agents autonomously interact and co-evolve, marks a pivotal shift toward Artificial General Intelligence (AGI). However, LLM-based multi-agent systems (LaMAS) are hindered by open-world issues such as scaling friction, coordination breakdown, and value dissipation. To address these challenges, we introduce Holos, a web-scale LaMAS architected for long-term ecological persistence. Holos adopts a five-layer architecture, with core modules primarily featuring the Nuwa engine for high-efficiency agent generation and hosting, a market-driven Orchestrator for resilient coordination, and an endogenous value cycle to achieve incentive compatibility. By bridging the gap between micro-level collaboration and macro-scale emergence, Holos hopes to lay the foundation for the next generation of the self-organizing and continuously evolving Agentic Web. We have publicly released Holos (accessible at https://holosai.io), providing a resource for the community and a testbed for future research in large-scale agentic ecosystems. |
| title | Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2604.02334 |