Evolutionary Emergence: The Struggle for Existence in Artificial Biota

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@PhdThesis{channon_ad_phdthesis,
  author =       "Alastair Channon",
  title =        "Evolutionary Emergence: The Struggle for Existence in
                 Artificial Biota",
  school =       "University of Southampton",
  year =         "2001",
  keywords =     "genetic algorithms, genetic programming, natural
                 selection",
  URL =          "http://www.channon.net/alastair/geb/phdthesis/channon_ad_phdthesis.pdf",
  address =      "UK",
  month =        nov,
  size =         "111 pages",
  abstract =     "The generation of complex entities with advantageous
                 behaviours beyond our manual design capability requires
                 long-term incremental evolution with continuing
                 emergence. This thesis presents the argument that
                 artificial selection models, such as traditional
                 genetic algorithms, are fundamentally inadequate for
                 this goal. Existing natural selection systems are
                 evaluated, revealing both significant achievements and
                 pitfalls. Thus, some requirements for the perpetuation
                 of evolutionary emergence are established. An
                 (artificial) environment containing simple virtual
                 autonomous organisms with neural controllers has been
                 created to satisfy these requirements and to aid in the
                 development of an accompanying theory of evolutionary
                 emergence. Resulting behaviours are reported alongside
                 their neural correlates. In one example, the collective
                 behaviour of one species provides a selective force
                 which is overcome by another species, demonstrating the
                 incremental evolutionary emergence of advantageous
                 behaviours via naturally-arising coevolution. Further
                 behavioural or neural analysis is infeasible in this
                 environment, so evolutionary statistical methods are
                 employed and extended in order to classify the
                 evolutionary dynamics. This qualitative analysis
                 indicates that evolution is unbounded in the system. As
                 well as validating the theory behind it, work with the
                 system has provided some useful lessons and directions
                 towards the evolution of increasingly complex
                 advantageous behaviours.",
}

Genetic Programming entries for Alastair D Channon

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