使用Petri网测量古代技术复杂性及其认知含义

Sebastian Fajardo, Paul R. B. Kozowyk, Geeske H. J. Langejans
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摘要

我们实现了一种计算机科学方法来解决旧石器时代考古学中的一个挑战:如何从物质文化中推断认知差异。考古物质文化与认知有关:更复杂的古代技术被认为需要复杂的认知。我们提出了一个应用Petri网分析来比较尼安德特人的焦油生产技术,并将结果与认知需求联系起来。我们将三种复杂性度量标准应用于建模的生产序列,每一种都依赖于它们自己独特的复杂性定义。基于这些结果,我们认为尼安德特人对工作记忆的要求可能与今天人类对工作记忆使用的偏好相似。这种方法还使我们能够区分高阶认知功能,这些功能结合了计划、抑制控制和学习等特征,这些特征可能是不同古代技术过程所需要的。Petri网方法可以帮助我们理解技术和认知进化,因为它可以用于不同的材料和技术,跨越时间和物种。
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Measuring ancient technological complexity and its cognitive implications using Petri nets
We implement a method from computer sciences to address a challenge in Paleolithic archaeology: how to infer cognition differences from material culture. Archaeological material culture is linked to cognition: more complex ancient technologies are assumed to have required complex cognition. We present an application of Petri net analysis to compare Neanderthal tar production technologies and tie the results to cognitive requirements. We applied three complexity metrics, each relying on their own unique definitions of complexity, to the modelled production sequences. Based on the results, we suggest that Neanderthal working memory requirements may have been similar to human preferences regarding working memory use today. This method also enables us to distinguish the high-order cognitive functions combining traits like planning, inhibitory control, and learnings that were likely required by different ancient technological processes. The Petri net approach can contribute to our understanding of technology and cognitive evolution as it can be used on different materials and technologies, across time and species.
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