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Evolution of genotype-phenotype mapping in a von Neumann self-reproduction within the platform of Tierra

Baugh, Declan and McMullin, Barry orcid logoORCID: 0000-0002-5789-2068 (2013) Evolution of genotype-phenotype mapping in a von Neumann self-reproduction within the platform of Tierra. In: European Conference on Complex Systems (ECCS) 2013, 16-20 Sept, 2013, Barcelona, Spain.

Abstract
John von Neumann first presented his theory of machine self-reproduction in the late 40's, in which he described a machine capable of performing the logical steps necessary to accommodate self-reproduction and provided an explanation in principle for how arbitrarily complex machines can construct other ("offspring") machine of equal or even greater complexity. This project implements the von Neumann architecture for self-reproduction within the pre-existing evolutionary platform of Tierra, which implements a (mutable) genotype-phenotype mapping during reproduction. Initially, the memory image of the automaton's genotype and phenotype are physically identical, and each symbol in memory may be interpreted as either as passive numerical data (g-symbol), or a functional instruction (p-symbol) depending on how the symbol is interpreted. If redundancy is introduced to a mutable genotype-phenotype mapping, the mapping system becomes non-invertible, rendering it impossible to compute an automaton's exact genotypic memory image by analysis of the phenotype alone. However, this non-invertible mapping may allow for a more robust genotype, increasing its robustness to fatal mutations and therefore increasing its ability to preserve its phenotypic form under perturbations.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:von Neumann; Genetic reproduction; Tierra; Artificial life; Genotype-phenotype mapping; Evolutionary growth of complexity
Subjects:Engineering > Artificial life
Computer Science > Computer simulation
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE)
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:IRCSET
ID Code:19536
Deposited On:14 Oct 2013 11:07 by Barry Mcmullin . Last Modified 01 Sep 2020 12:40
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