A key challenge in artificial intelligence (AI) is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex patterns, and uncovering previously unseen connections in vast scientific data. In this work, SciAgents, an approach that leverages three core concepts is presented: (1) large‐scale ontological knowledge graphs to organize and interconnect diverse scientific concepts, (2) a suite of large language models (LLMs) and data retrieval tools, and (3) multi‐agent systems with in‐situ learning capabilities. Applied to biologically inspired materials, SciAgents reveals hidden interdisciplinary relationships that were previously considered unrelated, achieving a scale, precision, and exploratory power that surpasses human research methods. The framework autonomously generates and refines research hypotheses, elucidating underlying mechanisms, design principles, and unexpected material properties. By integrating these capabilities in a modular fashion, the system yields material discoveries, critiques and improves existing hypotheses, retrieves up‐to‐date data about existing research, and highlights strengths and limitations. This is achieved by harnessing a “swarm of intelligence” similar to biological systems, providing new avenues for discovery. How this model accelerates the development of advanced materials by unlocking Nature's design principles, resulting in a new biocomposite with enhanced mechanical properties and improved sustainability through energy‐efficient production is shown.

中文翻译：

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SciAgents：通过 Bioinspired 多智能体智能图推理实现科学发现自动化


人工智能 （AI） 的一个关键挑战是创建能够通过探索新领域、识别复杂模式和在大量科学数据中发现以前看不见的联系来自主推进科学理解的系统。在这项工作中，SciAgents 提出了一种利用三个核心概念的方法：（1） 大规模本体论知识图谱来组织和互连不同的科学概念，（2） 一套大型语言模型 （LLMs） 和数据检索工具，以及 （3） 具有原位学习能力的多智能体系统。SciAgents 应用于受生物启发的材料，揭示了以前被认为无关的隐藏的跨学科关系，实现了超越人类研究方法的规模、精度和探索能力。该框架自主生成和完善研究假设，阐明潜在机制、设计原则和意想不到的材料特性。通过以模块化方式集成这些功能，该系统产生了材料发现、批评和改进现有假设，检索有关现有研究的最新数据，并突出了优势和局限性。这是通过利用类似于生物系统的“智能群”来实现的，为发现提供了新的途径。该模型如何通过解锁大自然的设计原则来加速先进材料的开发，从而通过节能生产产生具有增强机械性能和提高可持续性的新型生物复合材料。