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The contribution of the computational methodology to the empirical investigation of complex systems

机译:计算方法论对复杂系统的实证研究的贡献

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The framework of this article is the research into the methodology of complex systems' investigation, as defined in the complex epistemology developed by Edgar MORIN. A complex system is a meta-stable dynamical phenomenon implying many entities. It is produced and continuously maintained by circular processes. The circularity of those processes generates emerging properties among which the first is self-regulation and consequently a certain level of autonomy. Complex systems are very common phenomena in all day's life, but they remain unusual science objects. An overview of some influencing analytic and synthetic viewpoints in science and philosophy allows us presenting a few reasons of their inadequacy for dealing with complex systems. Empirical and social sciences have been especially subject to meet practical and theoretical difficulties in their investigations of such systems. We present a methodology where the investigation of a complex system is conducted progressively using theoretical and empirical knowledge about the real system, in conjunction with the construction of the simulation model and its results. That way, computerised simulation allows conducting further the hypothetical-deductive procedure and thus increasing the potential theoretical development of the empirical sciences dealing with complex systems. We call this procedure the computational methodology.
机译:本文的框架是对复杂系统研究方法的研究,这是由Edgar MORIN开发的复杂认识论所定义的。复杂的系统是隐含许多实体的亚稳态动力学现象。它是通过循环过程生产和连续维护的。这些过程的循环性产生了新兴的属性,其中首先是自我调节,因此具有一定程度的自主权。复杂系统是一生中非常普遍的现象,但它们仍然是不寻常的科学对象。对科学和哲学中一些具有影响力的分析和综合观点的概述,使我们能够提出一些不足以处理复杂系统的原因。经验和社会科学在研究此类系统时尤其遇到了实践和理论上的困难。我们提供一种方法,其中使用关于真实系统的理论和经验知识,结合仿真模型及其结果的构建,逐步研究复杂系统。这样,计算机模拟可以进一步进行假设演绎程序,从而增加了处理复杂系统的经验科学的潜在理论发展。我们称此程序为计算方法。

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