Evolving a Replicator The Genetic Programming of Self Reproduction in Cellular Automata

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{degaris:1993:erGPsrca,
  author =       "Hugo {de Garis}",
  title =        "Evolving a Replicator The Genetic Programming of Self
                 Reproduction in Cellular Automata",
  booktitle =    "ECAL-93 Self organisation and life: from simple rules
                 to global complexity",
  year =         "1993",
  pages =        "274--284",
  address =      "CP 231, Universite Libre de Bruxelles, Bld. du
                 Triomphe, 1050 Brussels, Belgium, Fax 32-2-659.5767
                 Phone 32-2-650.5776 Email sgross@ulb.ac.be",
  month =        "24--26 " # may,
  organisation = "Centre for Non-Linear Phenomena and Complex Systems",
  email =        "degaris@hip.att.co.jp",
  keywords =     "genetic algorithms, genetic programming,
                 nonotechnology, nanots, artificial life,
                 Qantum-electronic computers, Darwin machines",
  URL =          "http://www.iss.whu.edu.cn/degaris/papers/ECAL93.pdf",
  URL =          "http://citeseer.ist.psu.edu/521663.html",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.17.9218&rank=7",
  URL =          "http://alife.org/paper/ecal93/evolving-replicator-genetic-programming-self-reproduction-cellular-automata",
  URL =          "http://alife.org/sites/default/files/collections/ECAL93-0274-0284-De-Garis.pdf",
  size =         "11 pages",
  abstract =     "This paper presents the results of an investigative
                 study into the evolution of cellular automata
                 replicators using Genetic Programming (GP) techniques
                 (i.e. using Genetic Algorithms (GAs) to build/evolve
                 complex systems). There are at least two reasons why
                 such a study might be considered interesting. One
                 reason is to explore how difficult the evolution of
                 (CA) replicators might be, a topic of importance for
                 Artificial Life. Another reason is the possibility that
                 the evolution of CAs, if successful, may provide tools
                 for next-generation quantum-electronic computers (e.g.
                 using quantum dot arrays) which may use CAs as their
                 operating principle.",
  notes =        "Presents results from the evolution of cellular
                 automata replicators using GP (ie using GAs to
                 build/evolve systems. 1: How difficult is the evolution
                 of CA replicators (intersity to Artificial Life), 2:
                 Evolving CAs may provide tools for quantum-electronic
                 computers (eg quantum dot arrays)",
  notes =        "There seems to be some doubt as to wether ECAL-93 was
                 published. This copy from attendee. May 2014: see
                 CD-ROM version on alife.org/paper/ecal93 web pages.

                 GA chromosome is fixed (1024 * 4 CA state values)
                 encoding the CA state transition rules.

                 {"}Evolving CA replicators is much harder than
                 initially thought{"}

                 Now working on CA networks cf Von Neuman, Codd,
                 Burks.

                 At one point erroneously ascribed to ECAL-2013
                 \cite{deGaris:2013:ECAL}.",
}

Genetic Programming entries for Hugo de Garis

Citations