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frameworks have the same minute chance of banging out identical verse. Still, if a
novel mechanism is introduced for producing novel sonnets, that employs a typing
primate army, and it somehow works with a probability above that of random search
(for instance), then this would count as a creative event.
In answer then to the general question, “Is nature creative?” we would emphat-
ically claim, “Yes!” In many circumstances, with respect to many frameworks, na-
ture, especially the evolutionary process, is creative.
13.8 Realising Our Definition of Creativity in Software
As discussed above, there are a number of ways we might attempt to emulate the
creativity of nature by writing generative software: by modelling intelligence, life,
or even a complete open-ended evolving ecosystem. These are all approaches that
artists have tried, the last of them, open-ended evolution, is perhaps the most promis-
ing since by definition it refers to an evolutionary system's ability to inexhaustibly
generate novel frameworks. Yet an artificial system of this kind remains elusive. At
the time of writing nobody has convincingly demonstrated open-ended evolution in
software.
Whilst software-based open-ended evolution eludes us, some of the alternative
strategies mentioned have shown a little immediate promise for generative art. In
particular, artificial evolution of imagery, especially when assisted by human aes-
thetic assessment of fitness, has received much attention. In light of this, our cre-
ativity measure has been investigated as a means for automatically guiding the
evolution of simple line drawings (Kowaliw et al. 2009 ). This forms part of an
effort to improve the automatic and assisted creativity of evolutionary software.
Our definition is, in practice, computationally intensive to apply. Hence, for prac-
tical reasons, Kowaliw devised creativity-lite , a modification that is tractable and
testable against the full implementation of our measure. The output produced by the
creativity-lite measure has been tested against common-language understanding of
the term creativity by allowing users to evaluate automatically generated textural
images (Kowaliw et al. 2012 ). The results of this research are summarised below.
13.8.1 The Automatic Generation of Creative Biomorphs
In order to apply our definition to a practical task, Kowaliw et al. elected to gener-
ate stick figures based on the biomorphs of Dawkins ( 1989 ) and see if they could
automatically distinguish between those that were creative, and those that were not.
Biomorphs are intricate line drawings made of straight segments that may be over-
laid upon one another hundreds of times to generate rich patterns reminiscent of
trees, insects, snowflakes, stars or countless other forms. Each individual biomorph
can be considered, potentially, a creative generative system, since it is capable of
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