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bird or an insect (e.g. in evaluating mate selection) is all that is required for [compu-
tational] aesthetic evaluation:
This provides some hope for those who would follow a psychological path to computational
aesthetic evaluation, because creatures with simpler brains than man practice mate selection.
In this context, as suggested in [ 16 ], the tastes of the individual in male bower-
birds are made visible when they gather collections of bones, glass, pebbles, shells,
fruit, plastic and metal scraps from their environment, and arrange them to attract
females [ 10 ]:
They perform a mating dance within a specially prepared display court. The characteristics of
an individual's dance or artefact display are specific to the species, but also to the capabilities
and, apparently, the tastes of the individual.
However the question of whether 'mate selection behaviour in animals implies
making a judgement analogous to aesthetic judgement in humans' is perhaps (pace
Nagel's famous discussion 'What is it like to be a bat? '[ 27 ]) a fundamentally unan-
swerable question.
In contrast, the role of education (or training) in recognising 'good' and 'bad',
'creative' and 'non-creative' has been experimentally probed. A suggestive study
investigating this topic byWatanabe [ 39 ] gathers a set of children's paintings, and then
adult humans are asked to label the “good” from the “bad”. Pigeons are then trained
through operant conditioning to only peck at good paintings. After the training, when
pigeons are exposed to a novel set of already judged children's paintings, they show
their ability in the correct classification of the paintings.
This emphasises the role of learning training and raises the question on whether
humans are fundamentally trained (or “biased”) to distinguish good and/or creative
work.
Another tightly related topic to swarm intelligence in this context is the creativity
of social systems. Bown in [ 11 ] indicates that our creative capabilities are contingent
on the objects and infrastructure available to us, which help us achieve individual
goals, in two ways:
One way to look at this is, as Clark does [ 13 ], in terms of the mind being extended to a
distributed system with an embodied brain at the centre, and surrounded by various other
tools, from digits to digital computers. Another way is to step away from the centrality
of human brains altogether and consider social complexes as distributed systems involving
more or less cognitive elements.
Discussion on creativity and the conditions whichmake a particular work creative,
have generated heated debate amongst scientists and philosophers for many years
[ 31 ]; for a theoretical review on 'conditions of creativity'; the 'systems' view of
creativity; cognitive approaches, etc. see also [ 35 ]. Although this article does not aim
to resolve any of these issues (or even suggest that the presented work strongly fits
and endorses the category of the 'computationally creative realm'), we investigate the
performance of a swarm intelligence sketching systemwhich, we suggest, highlights
core issues inherent in exploring conceptual/artistic space(s).
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