Computational Discovery of Instructionless Self-Replicating Structures in Cellular Automata

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Zhijian Pan and James A. Reggia",
  title =        "Computational Discovery of Instructionless
                 Self-Replicating Structures in Cellular Automata",
  journal =      "Artificial Life",
  year =         "2010",
  volume =       "16",
  number =       "1",
  pages =        "39--63",
  month =        "Winter",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1530-9185",
  DOI =          "doi:10.1162/artl.2009.16.1.16104",
  abstract =     "Cellular automata models have historically been a
                 major approach to studying the information-processing
                 properties of self-replication. Here we explore the
                 feasibility of adopting genetic programming so that,
                 when it is given a fairly arbitrary initial cellular
                 automata configuration, it will automatically generate
                 a set of rules that make the given configuration
                 replicate. We found that this approach works
                 surprisingly effectively for structures as large as 50
                 components or more. The replication mechanisms
                 discovered by genetic programming work quite
                 differently than those of many past manually designed
                 replicators: There is no identifiable instruction
                 sequence or construction arm, the replicating
                 structures generally translate and rotate as they
                 reproduce, and they divide via a fission like process
                 that involves highly parallel operations. This makes
                 replication very fast, and one cannot identify which
                 descendant is the parent and which is the child. The
                 ability to automatically generate self-replicating
                 structures in this fashion allowed us to examine the
                 resulting replicators as their properties were
                 systematically varied. Further, it proved possible to
                 produce replicators that simultaneously deposited
                 secondary structures while replicating, as in some past
                 manually designed models. We conclude that genetic
                 programming is a powerful tool for studying
                 self-replication that might also be profitably used in
                 contexts other than cellular spaces.",
  notes =        "IBM Annapolis Lab, 1997 Annapolis Exchange Parkway,
                 Annapolis, MD 21401, USA. Computer Science Department,
                 University of Maryland, College Park, MD 20742, USA.",

Genetic Programming entries for Zhijian Pan James A Reggia