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Traditionally, complex systems have been analyzed using tools from nonlinear dynamics and statistical information theory. Recently, the analytical framework of complex networks has led to a significant reappraisal of commonalities and differences between complex systems found in different scientific domains (Amaral and Ottino, 2004). A key insight is that network topology, the graph structure of the interactions, places important constraints on the system's dynamics, by directing information flow, creating patterns of coherence between components, and by shaping the emergence of macroscopic system states. Complexity is highly sensitive to changes in network topology (Sporns et al., 2000). Changes in connection patterns or strengths may thus serve as modulators of complexity. The link between network structure and dynamics represents one of the most promising areas of complexity research in the near future.
Traditionally, complex systems have been analyzed using tools from nonlinear dynamics and statistical information theory. Recently, the analytical framework of complex networks has led to a significant reappraisal of commonalities and differences between complex systems found in different scientific domains (Amaral and Ottino, 2004). A key insight is that network topology, the graph structure of the interactions, places important constraints on the system's dynamics, by directing information flow, creating patterns of coherence between components, and by shaping the emergence of macroscopic system states. Complexity is highly sensitive to changes in network topology (Sporns et al., 2000). Changes in connection patterns or strengths may thus serve as modulators of complexity. The link between network structure and dynamics represents one of the most promising areas of complexity research in the near future.
传统上，复杂系统的分析一直使用非线性动力学和统计信息理论的工具。最近，复杂网络的分析学框架引发了对不同科学领域复杂系统之间共性和差异的重新评估(Amaral 和 Ottino，2004)。一个关键的洞察是网络拓扑——交互的图结构，通过引导信息流，创造组件之间的一致性模式，以及塑造宏观系统状态的涌现，对系统的动力学施加了重要的约束。复杂性对网络拓扑的变化高度敏感。因此，连接模式或强度的改变可以作为复杂性的调节器。网络结构与动力学之间的联系是近期复杂性研究中最有前途的领域之一。
==为什么是复杂性？==
==为什么是复杂性？==