神经网络的自适应进化
Adaptive evolution on neutral networks
摘要：
我们研究了大型但有限的无性种群的进化，在健身景观中，所有的突变是中性或强烈有害的。我们表明，尽管没有更高的健身基因型，适应发生的中性基因型分布更有利的地区被发现。由于这些发现通常是罕见的事件，人口动态可以细分为单独的时代，它们之间的快速过渡。在一个时期内，种群的平均适应度近似恒定。然而，时期之间的过渡通常伴随着平均适应度的显著增加。我们验证了我们的理论考虑与两个易于分析的位串模型。
英文摘要：
We study the evolution of large but finite asexual populations evolving in fitness landscapes in which all mutations are either neutral or strongly deleterious. We demonstrate that despite the absence of higher fitness genotypes, adaptation takes place as regions with more advantageous distributions of neutral genotypes are discovered. Since these discoveries are typically rare events, the population dynamics can be subdivided into separate epochs, with rapid transitions between them. Within one epoch, the average fitness in the population is approximately constant. The transitions between epochs, however, are generally accompanied by a significant increase in the average fitness. We verify our theoretical considerations with two analytically tractable bitstring models.
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