智能体AI正推动科研自动化，实现自主推理与决策。
Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions
- 构建能自主规划、推理的智能体系统，替代人工完成科研流程。
- 已在化学、生物、材料等领域实现文献综述、假说生成等突破。
- 适合关注人机协作科研的学者与科技政策制定者。
将智能体AI引入科学发现标志着研究自动化的新前沿。这些具备推理、规划和自主决策能力的AI系统，正在改变科学家进行文献综述、生成假说、开展实验和分析结果的方式。本综述全面概述了智能体AI在科学发现中的应用，对现有系统与工具进行分类，并总结了化学、生物学和材料科学等领域的最新进展。我们讨论了关键评估指标、实施框架及常用数据集，以深入理解该领域的现状。最后，针对文献综述自动化、系统可靠性与伦理问题等核心挑战展开分析，并提出未来研究方向，强调人机协同与系统校准的增强。
原文摘要 · Abstract (English)
The integration of Agentic AI into scientific discovery marks a new frontier in research automation. These AI systems, capable of reasoning, planning, and autonomous decision-making, are transforming how scientists perform literature review, generate hypotheses, conduct experiments, and analyze results. This survey provides a comprehensive overview of Agentic AI for scientific discovery, categorizing existing systems and tools, and highlighting recent progress across fields such as chemistry, biology, and materials science. We discuss key evaluation metrics, implementation frameworks, and commonly used datasets to offer a detailed understanding of the current state of the field. Finally, we address critical challenges, such as literature review automation, system reliability, and ethical concerns, while outlining future research directions that emphasize human-AI collaboration and enhanced system calibration.
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