语义知识引导创新,推动文化累积演化。
Semantic knowledge guides innovation and drives cultural evolution
- 用智能体模型与大规模实验结合,验证语义知识如何指导探索
- 有语义知识者创新成功率显著更高,且能迁移已有发现
- 适合对认知科学、文化演化感兴趣的读者
文化演化使思想与技术得以跨代积累,最终在人类中达到最复杂和开放的形式。尽管社会学习可传递创新成果,但其生成机制仍不明确。传统理论常将创新视为随机变异,难以解释人类文化的复杂性。本文提出,语义知识——即概念与其属性和功能之间的关联——驱动人类创新并推动累积文化发展。通过结合基于智能体的模型与大规模行为实验(N=1,243),我们发现:语义知识引导探索走向有意义解,提升创新成功率,并实现从已有发现中的泛化。此外,语义知识与社会学习协同作用,显著加速创新与文化累积。相比之下,缺乏语义知识的参与者表现仅如随机猜测,即使具备社会学习条件,也依赖浅层探索策略。结果表明,语义知识是人类累积文化的关键认知基础。
原文摘要 · Abstract (English)
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.
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