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使用 Petri 网测量古代技术的复杂性及其认知意义。

Measuring ancient technological complexity and its cognitive implications using Petri nets.

机构信息

Department of Materials Science and Engineering, Delft University of Technology, 2628 CD, Delft, Zuid-Holland, The Netherlands.

Palaeo-Research Institute, University of Johannesburg, Johannesburg, 2092, Gauteng, South Africa.

出版信息

Sci Rep. 2023 Sep 22;13(1):14961. doi: 10.1038/s41598-023-42078-1.

Abstract

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, and 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 modeled production processes. Based on the results, we propose that Neanderthal technical cognition may have been analogous to that of contemporary modern humans. This method also enables us to distinguish the high-order cognitive functions combining traits like planning, inhibitory control, and learning 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.

摘要

我们采用计算机科学领域的方法来解决旧石器考古学中的一个挑战

如何从物质文化推断认知差异。考古物质文化与认知有关,并且人们认为更复杂的古代技术需要复杂的认知。我们提出了一种使用 Petri 网分析来比较尼安德特人焦油生产技术的方法,并将结果与认知要求联系起来。我们将三种复杂性度量应用于建模的生产过程中,每种度量都依赖于自己独特的复杂性定义。根据结果,我们提出尼安德特人的技术认知可能与当代现代人的认知类似。这种方法还使我们能够区分需要不同古代技术过程的高阶认知功能,例如规划、抑制控制和学习等特质。Petri 网方法可以为我们理解技术和认知进化做出贡献,因为它可以应用于不同的材料和技术,跨越时间和物种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09f9/10516984/3f3d6f84393c/41598_2023_42078_Fig1_HTML.jpg

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