进化网络以获得更好的性能：突变和选择之间的妥协
Evolve Networks Towards Better Performance: a Compromise between Mutation and Selection
摘要：
自然选择和随机突变之间的相互作用是近年来经常争论的问题。类似的困境是否也存在于生物网络等真实网络的进化中？本文试图通过一个简单的模型系统来讨论这一问题，在这个模型系统中，网络的拓扑结构被反复修改和选择，以使它们在动态过程中具有更好的性能。有趣的是，当具有最佳性能的网络偏离纯突变下的稳态网络时，我们发现进化表现为突变和选择之间的平衡。当突变的时间尺度与动力学过程的时间尺度相当时，演化的稳态主要由突变决定。另一方面，当突变的时间尺度比动态过程的时间尺度长得多时，选择主导了进化，稳态网络变得具有更好的性能和高度异质性的结构。尽管我们的模型系统很简单，但这一发现可以为检测控制真实系统演化的潜在机制提供有用的指示。
英文摘要：
The interaction between natural selection and random mutation is frequently debated in recent years. Does similar dilemma also exist in the evolution of real networks such as biological networks? In this paper, we try to discuss this issue by a simple model system, in which the topological structure of networks is repeatedly modified and selected in order to make them have better performance in dynamical processes. Interestingly, when the networks with optimal performance deviate from the steady state networks under pure mutations, we find the evolution behaves as a balance between mutation and selection. Furthermore, when the timescales of mutations and dynamical processes are comparable with each other, the steady state of evolution is mainly determined by mutation. On the opposite side, when the timescale of mutations is much longer than that of dynamical processes, selection dominates the evolution and the steady-state networks turn to have much improved performance and highly heterogeneous structures. Despite the simplicity of our model system, this finding could give useful indication to detect the underlying mechanisms that rein the evolution of real systems.
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