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In the past four decades, computational sociology has been introduced and gaining popularity.  This has been used primarily for modeling or building explanations of social processes and are depending on the emergence of complex behavior from simple activities.  The idea behind emergence is that properties of any bigger system do not always have to be properties of the components that the system is made of.  The people responsible for the introduction of the idea of emergence are Alexander, Morgan, and Broad, who were classical emergentists.  The time at which these emergentists came up with this concept and method was during the time of the early twentieth century.  The aim of this method was to find a good enough accommodation between two different and extreme ontologies, which were reductionist materialism and dualism.  

In the past four decades, computational sociology has been introduced and gaining popularity.  This has been used primarily for modeling or building explanations of social processes and are depending on the emergence of complex behavior from simple activities.  The idea behind emergence is that properties of any bigger system do not always have to be properties of the components that the system is made of.  The people responsible for the introduction of the idea of emergence are Alexander, Morgan, and Broad, who were classical emergentists.  The time at which these emergentists came up with this concept and method was during the time of the early twentieth century.  The aim of this method was to find a good enough accommodation between two different and extreme ontologies, which were reductionist materialism and dualism.  

在过去的四十年里，计算社会学诞生并且越来越受欢迎。这主要用于建模或构建社会过程的解释，并且依赖于从简单活动中'''涌现 Emergence'''的复杂行为。涌现背后的思想是，任何较大系统不总是必须和组成系统的部分具有一样的性质。引入涌现思想的人是亚历山大（Alexander）、摩根（Morgan）和布罗德（Broad），他们都是'''经典涌现主义者 Classical Emergentists'''。经典涌现主义者提出这个概念和方法的时间是在二十世纪初期。这种方法的目的是在还原论的唯物主义和二元论这两种不同的本体论之间找到一个足够好的调和。

在过去的四十年里，计算社会学诞生并且越来越受欢迎。这主要用于建模或构建社会过程的解释，并且依赖于从简单活动中'''涌现 Emergence'''的复杂行为。涌现背后的思想是，任何较大系统不总是必须和组成系统的部分具有一样的性质。引入涌现思想的人是亚历山大 Alexander、摩根 Morgan和布罗德 Broad，他们都是'''经典涌现主义者 Classical Emergentists'''。经典涌现主义者提出这个概念和方法的时间是在二十世纪初期。这种方法的目的是在还原论的唯物主义和二元论这两种不同的本体论之间找到一个足够好的调和。

 

While emergence has had a valuable and important role with the foundation of Computational Sociology, there are those who do not necessarily agree.  One major leader in the field, Epstein, doubted the use because there were aspects that are unexplainable.  Epstein put up a claim against emergentism, in which he says it "is precisely the generative sufficiency of the parts that constitutes the whole's explanation".

While emergence has had a valuable and important role with the foundation of Computational Sociology, there are those who do not necessarily agree.  One major leader in the field, Epstein, doubted the use because there were aspects that are unexplainable.  Epstein put up a claim against emergentism, in which he says it "is precisely the generative sufficiency of the parts that constitutes the whole's explanation".

虽然涌现在计算社会学的建立上发挥了宝贵而重要的作用，但也有人不太同意。该领域的一个主要人物爱泼斯坦(Epstein)对这种用法持怀疑态度，因为有些方面是这个用法无法解释的。爱泼斯坦提出了一种反对“涌现主义”的观点，他表示:“正是这些部分的有生成意义的充分性构成了对整体的解释”。

虽然涌现在计算社会学的建立上发挥了宝贵而重要的作用，但也有人不太同意。该领域的一个主要人物爱泼斯坦 Epstein对这种用法持怀疑态度，因为有些方面是这个用法无法解释的。爱泼斯坦提出了一种反对“涌现主义”的观点，他表示:“正是这些部分的有生成意义的充分性构成了对整体的解释”。

Agent-based models have had a historical influence on Computational Sociology. These models first came around in the 1960s, and were used to simulate control and feedback processes in organizations, cities, etc.  During the 1970s, the application introduced the use of individuals as the main units for the analyses and used bottom-up strategies for modeling behaviors.  The last wave occurred in the 1980s.  At this time, the models were still bottom-up; the only difference is that the agents interact interdependently.

Agent-based models have had a historical influence on Computational Sociology. These models first came around in the 1960s, and were used to simulate control and feedback processes in organizations, cities, etc.  During the 1970s, the application introduced the use of individuals as the main units for the analyses and used bottom-up strategies for modeling behaviors.  The last wave occurred in the 1980s.  At this time, the models were still bottom-up; the only difference is that the agents interact interdependently.

'''基于主体的模型Agent-based Models'''对计算社会学有着历史性的影响。这些模型最早出现在20世纪60年代，用于仿真模拟组织、城市等系统的控制和反馈过程。在20世纪70年代，应用程序引入个体作为主要的分析单元，并使用自下而上的策略来对行为建模。最后一波浪潮发生在20世纪80年代。那时，模型仍然是自下而上的; 唯一的区别是主体之间具有互相依赖和相互作用。

'''基于主体的模型 Agent-based Models'''对计算社会学有着历史性的影响。这些模型最早出现在20世纪60年代，用于仿真模拟组织、城市等系统的控制和反馈过程。在20世纪70年代，应用程序引入个体作为主要的分析单元，并使用自下而上的策略来对行为建模。最后一波浪潮发生在20世纪80年代。那时，模型仍然是自下而上的; 唯一的区别是主体之间具有互相依赖和相互作用。

===Systems theory and structural functionalism 系统理论和结构功能主义===

===Systems theory and structural functionalism 系统理论和结构功能主义===

By the late 1960s and early 1970s, social scientists used increasingly available computing technology to perform macro-simulations of control and feedback processes in organizations, industries, cities, and global populations. These models used differential equations to predict population distributions as holistic functions of other systematic factors such as inventory control, urban traffic, migration, and disease transmission. Although simulations of social systems received substantial attention in the mid-1970s after the Club of Rome published reports predicting that policies promoting exponential economic growth would eventually bring global environmental catastrophe, the inconvenient conclusions led many authors to seek to discredit the models, attempting to make the researchers themselves appear unscientific. Hoping to avoid the same fate, many social scientists turned their attention toward micro-simulation models to make forecasts and study policy effects by modeling aggregate changes in state of individual-level entities rather than the changes in distribution at the population level. However, these micro-simulation models did not permit individuals to interact or adapt and were not intended for basic theoretical research.

By the late 1960s and early 1970s, social scientists used increasingly available computing technology to perform macro-simulations of control and feedback processes in organizations, industries, cities, and global populations. These models used differential equations to predict population distributions as holistic functions of other systematic factors such as inventory control, urban traffic, migration, and disease transmission. Although simulations of social systems received substantial attention in the mid-1970s after the Club of Rome published reports predicting that policies promoting exponential economic growth would eventually bring global environmental catastrophe, the inconvenient conclusions led many authors to seek to discredit the models, attempting to make the researchers themselves appear unscientific. Hoping to avoid the same fate, many social scientists turned their attention toward micro-simulation models to make forecasts and study policy effects by modeling aggregate changes in state of individual-level entities rather than the changes in distribution at the population level. However, these micro-simulation models did not permit individuals to interact or adapt and were not intended for basic theoretical research.

截至20世纪60年代末70年代初，社会科学家越来越多地使用已有的计算技术，在组织、工业、城市和全球人口中进行控制和反馈过程的'''宏观模拟 Macrosimulation''' 。这些模型使用微分方程作为其他系统因素的整体函数来预测人口分布，这些系统因素包括库存控制、城市交通、人口迁移和疾病传播等。20世纪70年代中期，罗马俱乐部(Club of Rome)发表报告预测，促进指数式经济增长的政策最终将导致全球环境灾难，这些令人不舒服的结论导致许多研究者试图反驳这些模型，试图让研究人员自己显得不那么科学。

截至20世纪60年代末70年代初，社会科学家越来越多地使用已有的计算技术，在组织、工业、城市和全球人口中进行控制和反馈过程的'''宏观模拟 Macrosimulation''' 。这些模型使用微分方程作为其他系统因素的整体函数来预测人口分布，这些系统因素包括库存控制、城市交通、人口迁移和疾病传播等。20世纪70年代中期，'''罗马俱乐部 Club of Rome''' 发表报告预测，促进指数式经济增长的政策最终将导致全球环境灾难，这个悲观的结论导致许多研究者试图反驳这些模型，并试图让研究显得不那么科学。

   --[[用户:趣木木|趣木木]]（[[用户讨论:趣木木|讨论]]），这些令人不舒服的结论导致许多研究者试图反驳这些模型，试图让研究人员自己显得不那么科学    这句话再看一看

   （--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） 根据意思，inconvenient译为悲观的，因为这个结论预示了悲观的未来，所以令指出这一点的科学家们感到inconvenient）

为了避免同样的情况，许多社会科学家将注意力转向'''微观模拟 Microsimulation'''模型。这些模型通过模拟个体状态的总体变化而不是总体人口级别的变化来进行预测和研究政策的效果。然而，这些微观模拟模型并不允许个体相互作用或适应、变化（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）变化是根据适应（adapt）加上去的，不知道是否合理），研究者也不打算将它们用于基础理论研究。

为了避免同样的情况，许多社会科学家将注意力转向'''微观模拟 Microsimulation'''模型。这些模型通过模拟个体状态的总体变化而不是总体人口级别的变化来进行预测和研究政策的效果。然而，这些微观模拟模型并不允许个体相互作用或适应、变化（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）变化是根据适应（adapt）加上去的，不知道是否合理），研究者也不打算将它们用于基础理论研究。