标题： 人工智能驱动的自动化可以成为下一代科学研究的基础 显示英文标题

标题： AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research

摘要： 科学学（SoS）探索科学研究发现背后的机制，并为提高科学研究效率和促进创新提供有价值的见解。传统方法通常依赖于简单化的假设和基本的统计工具，例如线性回归和基于规则的仿真，这些方法难以捕捉现代研究生态系统中的复杂性和规模。 人工智能（AI）的到来为下一代科学学提供了变革性的机会，使大规模模式发现自动化成为可能，并揭示了之前无法获得的见解。 本文对未来将科学学与人工智能结合以实现研究模式自动发现的整合提供了前瞻性的视角，并强调了可以从人工智能中大大受益的关键开放挑战。 我们概述了人工智能相对于传统方法的优势，讨论了潜在的局限性，并提出了克服它们的途径。 此外，我们展示了一个初步的多智能体系统作为模拟研究社会的示例，展示了人工智能复制现实世界研究模式的能力以及加速科学学研究进展的能力。 显示英文摘要

摘要： The Science of Science (SoS) explores the mechanisms underlying scientific discovery, and offers valuable insights for enhancing scientific efficiency and fostering innovation. Traditional approaches often rely on simplistic assumptions and basic statistical tools, such as linear regression and rule-based simulations, which struggle to capture the complexity and scale of modern research ecosystems. The advent of artificial intelligence (AI) presents a transformative opportunity for the next generation of SoS, enabling the automation of large-scale pattern discovery and uncovering insights previously unattainable. This paper offers a forward-looking perspective on the integration of Science of Science with AI for automated research pattern discovery and highlights key open challenges that could greatly benefit from AI. We outline the advantages of AI over traditional methods, discuss potential limitations, and propose pathways to overcome them. Additionally, we present a preliminary multi-agent system as an illustrative example to simulate research societies, showcasing AI's ability to replicate real-world research patterns and accelerate progress in Science of Science research.