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The Emergence of Pathological Constructors When Implementing the von Neumann Architecture for Self-reproduction in Tierra

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7426))

Abstract

John von Neumann’s architecture for genetic reproduction provides an explanation in principle for how arbitrarily complex machines can construct other (“offspring”) machines of equal or even greater complexity. We designed a von Neumann style self-reproducing ancestor, within the framework of the Tierra platform, which implements a (mutable) genotype-phenotype mapping during reproduction. However, we have consistently observed a particular phenomenon where what we call pathological constructors quickly emerge, which ultimately lead to catastrophic ecosystem collapse. Pathological constructors are creatures which rapidly construct multiple short malfunctioning offspring within their lifetime. Pathological constructors are a hindrance to an ecosystem because their offspring, although sterile, still occupy both memory space and CPU time. When several pathological constructors coincide in time, their production rate can be so high that their non-functional offspring displace the entire population of functional self-reproducing creatures, resulting in ecosystem collapse. We investigate the origin of pathological constructors, and consider how a more mutational robust architecture which is less susceptible to the emergence of these creatures can be created.

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© 2012 Springer-Verlag Berlin Heidelberg

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Baugh, D., McMullin, B. (2012). The Emergence of Pathological Constructors When Implementing the von Neumann Architecture for Self-reproduction in Tierra. In: Ziemke, T., Balkenius, C., Hallam, J. (eds) From Animals to Animats 12. SAB 2012. Lecture Notes in Computer Science(), vol 7426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33093-3_24

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  • DOI: https://doi.org/10.1007/978-3-642-33093-3_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33092-6

  • Online ISBN: 978-3-642-33093-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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