Long-term evolutionary dynamics in heterogeneous cellular automata

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "David Medernach and Taras Kowaliw and Conor Ryan and 
                 Rene Doursat",
  title =        "Long-term evolutionary dynamics in heterogeneous
                 cellular automata",
  booktitle =    "GECCO '13: Proceeding of the fifteenth annual
                 conference on Genetic and evolutionary computation
  year =         "2013",
  editor =       "Christian Blum and Enrique Alba and Anne Auger and 
                 Jaume Bacardit and Josh Bongard and Juergen Branke and 
                 Nicolas Bredeche and Dimo Brockhoff and 
                 Francisco Chicano and Alan Dorin and Rene Doursat and 
                 Aniko Ekart and Tobias Friedrich and Mario Giacobini and 
                 Mark Harman and Hitoshi Iba and Christian Igel and 
                 Thomas Jansen and Tim Kovacs and Taras Kowaliw and 
                 Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and 
                 John McCall and Alberto Moraglio and 
                 Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and 
                 Gustavo Olague and Yew-Soon Ong and 
                 Michael E. Palmer and Gisele Lobo Pappa and 
                 Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and 
                 Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and 
                 Daniel Tauritz and Leonardo Vanneschi",
  isbn13 =       "978-1-4503-1963-8",
  pages =        "231--238",
  keywords =     "genetic algorithms, genetic programming",
  month =        "6-10 " # jul,
  organisation = "SIGEVO",
  address =      "Amsterdam, The Netherlands",
  DOI =          "doi:10.1145/2463372.2463395",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "In this work we study open-ended evolution through the
                 analysis of a new model, HetCA, for 'heterogeneous
                 cellular automata'. Striving for simplicity, HetCA is
                 based on classical two-dimensional CA, but differs from
                 them in several key ways: cells include properties of
                 'age', 'decay', and 'quiescence'; cells use a
                 heterogeneous transition function, one inspired by
                 genetic programming; and there exists a notion of
                 genetic transfer between adjacent cells. The cumulative
                 effect of these changes is the creation of an evolving
                 ecosystem of competing cell colonies. To evaluate the
                 results of our new model, we define a measure of
                 phenotypic diversity on the space of cellular automata.
                 Via this measure, we contrast HetCA to several controls
                 known for their emergent behaviours---homogeneous CA
                 and the Game of Life---and several variants of our
                 model. This analysis demonstrates that HetCA has a
                 capacity for long-term phenotypic dynamics not readily
                 achieved in other models. Runs exceeding one million
                 time steps do not exhibit stagnation or even cyclic
                 behaviour. Further, we show that the design choices are
                 well motivated, as the exclusion of any one of them
                 disrupts the long-term dynamics.",
  notes =        "Also known as \cite{2463395} GECCO-2013 A joint
                 meeting of the twenty second international conference
                 on genetic algorithms (ICGA-2013) and the eighteenth
                 annual genetic programming conference (GP-2013)",

Genetic Programming entries for David Medernach Taras Kowaliw Conor Ryan Rene Doursat