Cultural evolution allows ideas and technologies to accumulate across generations, reaching their most complex and open-ended form in humans. While social learning enables the transmission of such innovations, the cognitive processes that generate them remain poorly understood. Classical theories typically treat innovation as random variation, a simplification insufficient for explaining the complexity of human cultural evolution. We propose that semantic knowledge-the associations linking concepts to their properties and functions-guides human innovation and drives cumulative culture. To test this, we combined an agent-based model, which examines how semantic knowledge shapes cultural evolutionary dynamics, with a large-scale behavioral experiment (N = 1,243) testing its role in human innovation. Across both approaches, we found that semantic knowledge directed exploration toward meaningful solutions, enhanced innovation success, and enabled generalization from prior discoveries. Moreover, semantic knowledge interacted synergistically with social learning to amplify innovation and accelerate cumulative cultural change. In contrast, experimental participants lacking access to semantic knowledge performed no better than chance, even when social learning was possible, and relied on shallow exploration strategies for innovation. Together, these findings suggest that semantic knowledge is a key cognitive process underpinning human cumulative culture.

翻译：文化演化使得思想和技术能够代际累积，在人类身上达到最为复杂和开放的形式。尽管社会性学习能够传播此类创新，但产生创新的认知过程仍鲜为人知。经典理论通常将创新视为随机变异，这种简化不足以解释人类文化演化的复杂性。我们提出，语义知识——将概念与其属性及功能关联起来的联想——引导着人类创新并驱动累积文化。为验证这一假说，我们结合了基于主体的模型（用于考察语义知识如何塑造文化演化动态）与大规模行为实验（N=1,243，用于检验其在人类创新中的作用）。在这两种方法中，我们发现：语义知识引导探索走向有意义的解决方案，提升创新成功率，并实现从先前发现中泛化。此外，语义知识与社会性学习产生协同效应，放大创新并加速累积性文化变迁。相反，缺乏语义知识的实验参与者即使能够进行社会性学习，其表现也不优于随机水平，且依赖浅层探索策略进行创新。综合来看，这些发现表明，语义知识是支撑人类累积性文化的关键认知过程。