AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning
The paper introduces AgentFugue, a framework designed for scaling agent capabilities in long-horizon tasks through collective reasoning. It emphasizes the potential of multiple peer agents working in parallel to enhance task performance without centralized planning. The findings suggest that this approach can yield significant capability gains compared to traditional methods.
- ▪AgentFugue is built around a shared reasoning hub that facilitates communication among peer agents.
- ▪The framework allows agents to access and utilize discoveries made by others, enhancing their individual search processes.
- ▪The study demonstrates that collective reasoning can improve performance in challenging long-horizon settings.
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Computer Science > Artificial Intelligence arXiv:2605.24486 (cs) [Submitted on 23 May 2026] Title:AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning Authors:Yuyang Hu, Hongjin Qian, Shuting Wang, Jiongnan Liu, Tong Zhao, Xiaoxi Li, Zheng Liu, Zhicheng Dou View a PDF of the paper titled AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning, by Yuyang Hu and 7 other authors View PDF HTML (experimental) Abstract:Recent progress on long-horizon agentic tasks has been driven largely by scaling up individual agents through stronger models, better tools, and more effective scaffolding.
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