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🧠 AI🟢 BullishImportance 7/10
Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web
arXiv – CS AI|Xiaohang Nie, Zihan Guo, Zicai Cui, Jiachi Yang, Zeyi Chen, Leheyi De, Yu Zhang, Junwei Liao, Bo Huang, Yingxuan Yang, Zhi Han, Zimian Peng, Linyao Chen, Wenzheng Tom Tang, Zongkai Liu, Tao Zhou, Botao Amber Hu, Shuyang Tang, Jianghao Lin, Weiwen Liu, Muning Wen, Yuanjian Zhou, Weinan Zhang|
🤖AI Summary
Researchers introduce Holos, a web-scale multi-agent system designed to create an "Agentic Web" where AI agents can autonomously interact and evolve toward AGI. The system features a five-layer architecture with the Nuwa engine for agent generation, market-driven coordination, and incentive compatibility mechanisms.
Key Takeaways
- →Holos addresses scaling friction, coordination breakdown, and value dissipation issues in LLM-based multi-agent systems.
- →The system features a five-layer architecture with the Nuwa engine for high-efficiency agent generation and hosting.
- →A market-driven Orchestrator provides resilient coordination between agents in the ecosystem.
- →The platform includes an endogenous value cycle to achieve incentive compatibility among agents.
- →Holos is publicly accessible at holosai.io as a testbed for future agentic ecosystem research.
#multi-agent-systems#llm#agi#agentic-web#ai-coordination#web-scale#artificial-intelligence#research#ecosystem
Read Original →via arXiv – CS AI
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