从语义记忆到集体创造力：一种生成认知基础的社会创造力模型
From semantic memory to collective creativity: A generative cognitive foundation for social creativity models
AI总结：
本文提出一个多层社会认知智能体框架，通过调节语义模ularity生成个体差异，揭示集体创造力中的认知与社会结构机制。
摘要：
基于模拟的理论发展通过将社会结构与涌现结果联系起来，为集体表现提供了有力的见解，但其在集体创造力方面的扩展却面临困难。创造力难以在纯社会层面捕捉，因为新颖的想法是通过认知机制生成的。为解决这一差距，我们引入了一个多层社会认知智能体框架，其中智能体共享共同的语义词汇和基质，但语义网络拓扑结构不同。一个生成性参数调节语义模ularity，产生出涌现的个体差异在想法广度上。当智能体交换想法痕迹时，两种经典的社交创造力现象出现，而无需被强加：在交互前想法重叠较低预测了更大的刺激收益，而共享的灵感来源诱导了网络层面的冗余。该框架使能够关于集体创造力中的认知和社会结构进行机制性理论构建。
英文摘要：
Simulation-based theory development has yielded powerful insights into collective performance by linking social structure to emergent outcomes, yet it has struggled to extend to collective creativity. Creativity is hard to capture purely at the social level, as novel ideas are generated through cognitive mechanisms. To address this gap, we introduce a multi-level socio-cognitive agent-based framework in which agents share a common semantic vocabulary and substrate but differ in semantic network topology. A single generative parameter tunes semantic modularity, yielding emergent individual differences in ideational breadth. When agents exchange ideation traces, two canonical social-creativity phenomena arise without being imposed: lower pre-interaction ideation overlap predicts larger stimulation gains, and shared inspiration sources induce network-level redundancy. The framework enables mechanistic theory-building about cognition and social structure in collective creativity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
