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文化的散布——注释:

2020年6月19日  来源:合作的复杂性:基于参与者竞争与合作的模型 作者:(美)罗伯特·阿克塞尔罗德 提供人:yanjia82......

注释:

[1]一个例外是卡利(Carley,1991)关于知识传播的模型。在这个模型中,除非不同社群的成员最初没有共享的知识,社群差异消失了。另一个例外是博伊德和理奇森(Boyd and Richerson,1985)的间接偏见模型,它允许一个文化特性的吸引力受控制性的影响。但是即使在这个模型中,只有一个文化特性被考虑。

[2]爱泼斯坦和阿克西泰尔的糖域(Sugarscape)模型非常广泛,包括贸易、移民、战争、疾病和交配。例如,类似文化的行动者被允许配偶,不同文化的行动者被允许战斗。

[3]在政治学中的参与者模型通常强调冲突的过程(诸如战争和军事联盟)而不是社会影响。例如Bremer and Mihalka,1977;Schrodt,1981;Cusack and Stoll,1990;Axelrod,1995;Cederman,1991。涉及社会影响的代理模型包括Huckfeldt and Sprague,1991;Brown and McBurnett,1993。一个广范围的代理模型是Epstein and Axtell,1996。

[4]对那些偏好对称的国家而言,这里对文化c是如何变化的有一个完整的描述。随机选择一个点(s),它随机的邻居(n),还有一个随机的特征(f)。设定G(s,n)是特征的集合,其中元素是g,那么文化特征就是不平等的,比如c(s,g)≠c(n,g)。如果c(s,f)=c(n,f)且G并非空集,那么在G(s,n)中随机选择一个特性g,重新设定c(s,g)为c(n,g)。这在模型里就意味着一个随机特征f是两个点共同传统的概率,等于这两个点之间的文化相似程度。

[5]这个模拟操作时一次发生一个事件以避免点同时移动造成的人造物品,可以参见Huberman and Glance,1993。

[6]模型能被视为彼此具有吸引力国家的马尔可夫过程。不幸的是,分析马尔可夫过程的数学工具,诸如特征值等,在这种情况下是不能用的,因为动态机制太复杂了。例如,在表7.1中给定的这次模拟中可能的国家数目是10500,这比宇宙中原子的数目要多得多。其他能被看作马尔可夫过程的代理模型也得诉诸计算机模拟(e.g.,Bremer and Mihalka,1977;Schrodt,1981;Cusack and Stoll,1990)。

[7]模型用Pascal语言编码。在Macintosh Quadra 700上运行,在图7.1中显示的运行花费了11秒。

[8]这是说明什么叫路径依赖(path dependence)的一个很好例子(比如Arthur,1988)。

[9]技术上,如果邻近的两个点有一个通道,以至于每一个点和它相邻的点在通道上至少有1个特征相同,那么这两个点在同一地带中。

[10]注意到对于图7.3,参数是为了产生相对大的稳定区域数目而选择的。在这些参数情况下,10×10的版图中平均的稳定区域数目是18.6,而在100×100的版图中,平均的稳定区域数目则是2.1。(参见图7.2。在图7.2中10×10的版图下稳定区域的数目和表7.1中相应单元的轻微差异是基于不同的演示。)

[11]较大的邻居导致较少的稳定区域的事实暗示着,活动性将导致较少的稳定区域。这在使用阿克西泰尔等的模型的模拟中得到了证实(Axtell et al.,1996)。

[12]希望探讨这个模型和该模型其他扩展的读者,可以访问这个网址:http://pscs.physics.lsa.umich.edu/Software/ComplexCoop.html获取源代码和文件。在那个网页可以链接到“散布文化”(Disseminating Culture)的其他主题。

[13]每个特征具有两个特性,对于每个点而言,唯一稳定的结果是要么存在和邻居同样的文化,要么存在和邻居完全不同、互为补充的文化。因为对补充文化的补充就是初始的文化,所以在所有稳定的区域中至多有两种文化可能。

[14]这个结果通过允许每一个参与者和其他参与者相互影响,已被目前的模型所证实(Axtell et al.,1996)。

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(1) 文章来源于Robert Axelrod,“The Dissemination of Culture:A Model with Local Convergence and Global Polarization,”Journal of Conflict Resolution 41(1997):203-226。经授权转载,授权方:Sage Publications,Inc.。

笔者感谢以下各位的帮助:克里斯·阿成(Chris Archen)、戴维·阿克塞尔罗德(David Axelrod)、罗布·阿克西泰尔(Rob Axtell)、斯科特·贝内特、阿瑟·伯克斯(Arthur Burks)、拉斯埃里克·锡德曼(Lars-Erik Cederman)、迈克尔·科恩、保罗·库兰特(Paul Courant)、乔舒亚·爱泼斯坦(Joshua Epstein)、杰伊·哈林顿(Jay Harrington)、拉里·赫希菲尔德(Larry Hirschfeld)、约翰·霍兰、戴维·拉扎尔(Dawid Lazer)、罗伯特·帕尔(Robert Pahre)、里克·里奥洛(Rick Riolo)、卡尔·西蒙(Carl Simon)和丹·斯珀伯(Dan Sperber)。本项目经费赞助来自Santa Fe Institute,Project 2050,以及LS&A Enrichment Fund of the University of Michigan。

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