Collective Computation,Information Flow,and the Emergence of Hunter-Gatherer Small-Worlds

作     者：Marcus J.Hamilton 

作者机构：the Department of AnthropologyUniversity of Texas at San AntonioSan AntonioTX 78249USA. 

出 版 物：《Journal of Social Computing》 (社会计算（英文）)

年 卷 期：2022年第3卷第1期

页      面：18-37页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：complex adaptive systems hierarchically modular networks collective brains macroecology allometry mammals primates 

摘      要：Two key features of human sociality are anatomically complex brains with neuron-dense cerebral cortices,and the propensity to form complex social networks with *** brains and complex social networks facilitate flows of fitness-enhancing energy and information at multiple scales of social ***,we consider how these flows interact to shape the emergence of macroscopic regularities in hunter-gatherer macroecology relative to other mammals and non-human *** computation is the processing of information by complex adaptive systems to generate inferences in order to solve adaptive *** hunter-gatherer societies the adaptive problem is to resolve uncertainty in generative models used to predict complex environments in order to maximize inclusive *** macroecological solution is to link complex brains in social networks to form collective brains that perform collective *** developing theory and analyzing data,the author shows hunter-gatherers bands of~16 people,or~4 co-residing families,form the largest collective brains of any social ***,because individuals,families,and bands interact at multiple time scales,these fission-fusion dynamics lead to the emergence of the macroscopic regularities in hunter-gatherer macroecology we observe in cross-cultural *** results show how computation is distributed across spatially-extended social networks forming decentralized knowledge systems characteristic of hunter-gatherer *** flow of information at scales far beyond daily interactions leads to the emergence of small-worlds where highly clustered local interactions are embedded within much larger,but sparsely connected multilevel metapopulations.