arXiv:2510.13081cs.MAcs.AI2025-10被引 4
用协作智能体闭环自主发现，突破人类决策瓶颈。
Agentic Discovery: Closing the Loop with Cooperative Agents
- 设计协作智能体系统，自动完成假设生成与实验设计。
- 通过闭环反馈提升科学发现效率，减少人工干预。
- 适合自动化科研、智能实验平台等场景的开发者。
随着数据驱动方法、人工智能和自动化工作流加速科学任务，发现速度日益受限于人类在设定目标、生成假设和设计实验等方面的决策负担。我们提出，需要协作智能体来增强人类角色，实现自主发现。实现此类智能体需在人工智能与基础设施方面取得进展。
原文摘要 · Abstract (English)
As data-driven methods, artificial intelligence (AI), and automated workflows accelerate scientific tasks, we see the rate of discovery increasingly limited by human decision-making tasks such as setting objectives, generating hypotheses, and designing experiments. We postulate that cooperative agents are needed to augment the role of humans and enable autonomous discovery. Realizing such agents will require progress in both AI and infrastructure.
智能体自主发现科研自动化
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。