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具有图灵机的进化模型。

Evolutionary model with Turing machines.

作者信息

Feverati Giovanni, Musso Fabio

机构信息

Laboratoire de Physique Theorique LAPTH, CNRS, UMR 5108, associé à l'Université de Savoie, 9, Chemin de Bellevue, Boîte Postale 110, 74941, Annecy le Vieux Cedex, France.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2008 Jun;77(6 Pt 1):061901. doi: 10.1103/PhysRevE.77.061901. Epub 2008 Jun 3.

Abstract

The development of a large noncoding fraction in eukaryotic DNA and the phenomenon of the code bloat in the field of evolutionary computations show a striking similarity. This seems to suggest that (in the presence of mechanisms of code growth) the evolution of a complex code cannot be attained without maintaining a large inactive fraction. To test this hypothesis we performed computer simulations of an evolutionary toy model for Turing machines, studying the relations among fitness and coding versus noncoding ratio while varying mutation and code growth rates. The results suggest that, in our model, having a large reservoir of noncoding states constitutes a great (long term) evolutionary advantage.

摘要

真核生物DNA中大量非编码部分的发展以及进化计算领域中代码膨胀的现象显示出惊人的相似性。这似乎表明(在存在代码增长机制的情况下),如果不维持一个大的非活性部分,就无法实现复杂代码的进化。为了验证这一假设,我们对图灵机的进化玩具模型进行了计算机模拟,在改变突变率和代码增长率的同时,研究了适应度与编码率和非编码率之间的关系。结果表明,在我们的模型中,拥有大量非编码状态的储备构成了巨大的(长期)进化优势。

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