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philosophically by the amount of income it generates, the number of publications
that cite their work or the number and importance of other artists who reference it.
Of course these are, in fact, the ways in which nearly all artistic achievements are
judged. However, these are not the only approaches available to us.
Many have tried to write creative software by adopting an Artificial Intelligence
approach. Their success may then be judged based on the perception that the re-
sults are as creative as those that might have been produced by a human in the same
domain, perhaps by using some of the criteria just listed. For instance, Harold Co-
hen's AARON software explores the potential for machine creativity in the visual
arts; software written by Lenat (
1983
) targets creativity in the domains of mathe-
matical discovery. Also represented are logic (Colton
2001
) and scientific discovery
(Langley et al.
1987
). Others have tried to achieve creativity using an Artificial Life
approach in which the aim is to replicate the behaviour or artefacts of non-human
organisms. For instance, artists have created ant path drawings (Barrass
2006
)or
flocking visualisations (Eldridge
2009
). Mimicking biological evolution offers an-
other approach. This has been applied to music composition (e.g. Dahlstedt
1999
,
Berry et al.
2001
) and image production (e.g. Sims
1991
, Todd and Latham
1992
).
The success of these approaches can be judged according to how well the system
mimics or even extends the creativity of nature in its different guises. For instance,
can it create a range of coloured patterns as rich as those found on butterfly wings?
Can it create a diversity of forms as wide and interesting as those found in the mor-
phology of the insect world? Can it generate sonic textures as intricate and rich as
those heard in a tropical rainforest?
A few artists have built complete virtual, evolving ecosystems, the dynamics of
which, they argue, should be considered creative (e.g. McCormack
2001
, Saunders
and Gero
2002
,Dorin
2004
). In this approach, the software contains representations
of organisms that roam a virtual world, acquiring energy by consuming one an-
other or from abiotic sources such as sunlight or heat. These same virtual organisms
compete for mates and the resources needed to reproduce. Over simulated time, un-
successful organism designs become extinct and are replaced by an ever-changing
community of virtual creatures that are better adapted to their environment. The
viewer of such software might perceive the space and its inhabitants as a rich visual
display, or perhaps as a musical composition created by the layering of organism
calls. The aesthetic representation available to an audience of these works depends
on how the artist adapts the internal representation of the virtual world to an acces-
sible audio-visual experience.
Software systems like these can be considered
generative art
: a programmer
specifies an algorithm for execution on a computer and this is left to run, possibly
under the interactive guidance of a human, or perhaps independently. A continuing
dynamical process that emerges from the program, or a static artefact suitable for
human perception that results from its execution, forms the artwork. It is hoped, at
least implicitly, that this is creative.
It is probably fair to say that most artists are not explicitly concerned with mea-
suring the novelty of their system, nor are they concerned with the ways in which
their creativity might be assessed. Well, at least not until they are required to pro-
vide justification for their ongoing artistic endeavours! Regardless, in this chapter
