Heredity, complexity, and surprise: embedded self-replication and evolution in CA

Chris Salzberg, Hiroki Sayama

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

This paper reviews the history of embedded, evolvable self-replicating structures implemented as cellular automata systems. We relate recent advances in this field to the concept of the evolutionary growth of complexity, a term introduced by McMullin to describe the central idea contained in von Neumann's self-reproducing automata theory. We show that conditions for such growth are in principle satisfied by universal constructors, yet that in practice much simpler replicators may satisfy scaled-down - yet equally relevant - versions thereof. Examples of such evolvable self-replicators are described and discussed, and future challenges identified.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, Alfons G. Hoekstra, Bastien Chopard
PublisherSpringer Verlag
Pages161-171
Number of pages11
ISBN (Print)3540235965, 9783540235965
DOIs
Publication statusPublished - 2004 Jan 1
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3305
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Salzberg, C., & Sayama, H. (2004). Heredity, complexity, and surprise: embedded self-replication and evolution in CA. In P. M. A. Sloot, A. G. Hoekstra, & B. Chopard (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 161-171). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3305). Springer Verlag. https://doi.org/10.1007/978-3-540-30479-1_17