An evolutionary model with Turing machines
Quantitative Methods
2009-11-13 v1 Neural and Evolutionary Computing
Genomics
Abstract
The development of a large non-coding 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 can't 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/non-coding ratio while varying mutation and code growth rates. The results suggest that, in our model, having a large reservoir of non-coding states constitutes a great (long term) evolutionary advantage.
Cite
@article{arxiv.0711.3580,
title = {An evolutionary model with Turing machines},
author = {Giovanni Feverati and Fabio Musso},
journal= {arXiv preprint arXiv:0711.3580},
year = {2009}
}
Comments
16 pages, 7 figures