From Artificial Evolution to Artificial Life

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

@PhdThesis{TJTaylor:thesis,
  author =       "Timothy John Taylor",
  title =        "From Artificial Evolution to Artificial Life",
  school =       "Division of Informatics, University of Edinburgh",
  year =         "1999",
  address =      "UK",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://homepages.inf.ed.ac.uk/timt/papers/thesis/",
  URL =          "http://homepages.inf.ed.ac.uk/timt/papers/thesis/thesis.ps.gz",
  URL =          "http://homepages.inf.ed.ac.uk/timt/papers/thesis/thesis.pdf",
  URL =          "http://www.tim-taylor.com/papers/thesis/",
  size =         "317 pages",
  abstract =     "This work addresses the question: What are the basic
                 design considerations for creating a synthetic model of
                 the evolution of living systems (i.e. an `artificial
                 life' system)? It can also be viewed as an attempt to
                 elucidate the logical structure (in a very general
                 sense) of biological evolution. However, with no
                 adequate definition of life, the experimental portion
                 of the work concentrates on more specific issues, and
                 primarily on the issue of open-ended evolution. An
                 artificial evolutionary system called Cosmos, which
                 provides a virtual operating system capable of
                 simulating the parallel processing and evolution of a
                 population of several thousand self-reproducing
                 computer programs, is introduced. Cosmos is related to
                 Ray's established Tierra system, but there are a number
                 of significant differences. A wide variety of
                 experiments with Cosmos, which were designed to
                 investigate its evolutionary dynamics, are reported. An
                 analysis of the results is presented, with particular
                 attention given to the role of contingency in
                 determining the outcome of the runs. The results of
                 this work, and consideration of the existing literature
                 on artificial evolutionary systems, leads to the
                 conclusion that artificial life models such as this are
                 lacking on a number of theoretical and methodological
                 grounds. It is emphasised that explicit theoretical
                 considerations should guide the design of such models,
                 if they are to be of scientific value. An analysis of
                 various issues relating to self-reproduction,
                 especially in the context of evolution, is presented,
                 including some extensions to von Neumann's analysis of
                 self-reproduction. This suggests ways in which the
                 evolutionary potential of such models might be
                 improved. In particular, a shift of focus is
                 recommended towards a more careful consideration of the
                 phenotypic capabilities of the reproducing individuals.
                 Phenotypic capabilities fundamentally involve
                 interactions with the environment (both abiotic and
                 biotic), and it is further argued that the theoretical
                 grounding upon which these models should be based must
                 include consideration of the kind of environments and
                 the kind of interactions required for open-ended
                 evolution. A number of useful future research
                 directions are identified. Finally, the relevance of
                 such work to the original goal of modelling the
                 evolution of living systems (as opposed to the more
                 general goal of modelling open-ended evolution) is
                 discussed. It is suggested that the study of open-ended
                 evolution can lead us to a better understanding of the
                 essential properties of life, but only if the questions
                 being asked in these studies are phrased
                 appropriately.",
}

Genetic Programming entries for Tim Taylor

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