Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis
Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis
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DOI：
10.1007/978-3-642-53734-9_2
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发表时间：
2014-01-01
期刊：
影响因子：
--
通讯作者：
Gershenson, Carlos
中科院分区：
文献类型：
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作者：
Fernandez, Nelson;Maldonado, Carlos;Gershenson, Carlos
近几十年来，复杂系统的科学研究（Bar-Yam 1997; Mitchell 2009）要求我们的世界观发生范式转变（Gershenson et al. 2007; Heylighen et al. 2007）。传统上，科学是还原论的。然而，当组件由于相关的相互作用而难以分离时，就会出现复杂性。这些相互作用是相关的，因为它们产生了决定系统未来的新信息。这一事实有几个含义（Gershenson 2013）。
In recent decades, the scientific study of complex systems (Bar-Yam 1997; Mitchell 2009) has demanded a paradigm shift in our worldviews (Gershenson et al. 2007; Heylighen et al. 2007). Traditionally, science has been reductionistic. Still, complexity occurs when components are difficult to separate, due to relevantinteractions. These interactions are relevant because they generate novel informationwhich determines the future of systems. This fact has several implications (Gershenson 2013).