科学发现的进化智能：从进化计算到累积发现系统
Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systems
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中文总结 AI 辅助
介绍用于科学发现的进化智能，它通过五维分析框架，将候选优化与经验保留相联以维持探索，能转化搜索轨迹为科学洞察力，在多样发现模式中演示，还指出关键瓶颈及推进从进化计算到进化智能转变的路线图。
中文摘要 AI 辅助
人工智能正在将科学发现从特定任务的工作流程转向自主系统，该系统在开放式候选空间中通过实验和人类反馈来组织探索。进化计算为反馈驱动的发现提供了计算基础，但其主要专注于预定义问题的候选优化，而累积发现需要经验保留。本文引入用于科学发现的进化智能，它通过在进化周期中将候选优化与经验保留联系起来，来维持探索。还介绍了一个五维分析框架，阐明了进化智能如何将孤立的搜索轨迹转化为累积的科学洞察力，并在不同发现模式中进行了演示，最后指出了评估、过程可追溯性和共享基础设施方面的关键瓶颈，为推进从进化计算到进化智能的转变提供了路线图。
英文摘要
Artificial intelligence (AI) is shifting scientific discovery from task-specific workflows towards autonomous systems that organize exploration with experimental and human feedback in open-ended candidate spaces. Evolutionary computation (EC) provides a computational basis for feedback-driven discovery because population-based search can maintain diverse scientific candidates while steering exploration through accumulated evidence. However, EC predominantly focuses on candidate refinement for predefined problems, whereas cumulative discovery requires experience retention. To bridge this gap, this review introduces evolutionary intelligence (EI) for scientific discovery. EI characterizes scientific AI systems that sustain exploration by linking candidate refinement with experience retention across evolutionary cycles. We introduce a five-dimensional analytical framework that asks what evolves, how candidates change, why candidates are selected, where feedback originates, and when evolution occurs. This framework clarifies how EI transforms isolated search trajectories into cumulative scientific insight. We further demonstrate this paradigm across diverse discovery modes, from evolving concrete scientific entities to orchestrating automated research workflows. Finally, we identify critical bottlenecks regarding evaluation, process traceability, and shared infrastructure, providing a concrete roadmap for advancing the transition from EC to EI in scientific discovery.
发表机构
- Xidian University（西安电子科技大学）
机构由 AI 辅助整理，请以论文原文为准。
