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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.
Page last modified by Tim Taylor on 16 November 2005