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One of the biggest problems with our coevolutionary approach is that, by removing the
human influence from the critics (aside from those in the initial generation of folk-song
derived transition tables), the system can rapidly evolve its own unconstrained aesthetics.
After a few generations of coevolving songs and preferences, the female critics may be
pleased only by musical sequences that the human user would find worthless.
Todd and Werner suggest that adding some basic musical rules might encourage
diversity while also encouraging songs that are human-like. Additionally a learning
and cultural aspect could be added by allowing individual females to change their
transition tables based on the songs they hear (Todd and Werner
1998
).
Greenfield (
2008b
) has presented an overview of coevolutionary methods used
in evolutionary art including some unpublished systems made by Steven Rooke.
Rooke first evolved critics by training them to match his manually given scores
for a training set of images. The critics then coevolve with new images. Individual
critics are scored by comparing their evaluations to those of previous critics. Critics
are maintained over time in a sliding window of 20 previous generations. Rooke
found that while the coevolved critics duplicated his taste, the overall system didn't
innovate by exploring new forms.
Greenfield then describes his own system where images and 10
10 convolu-
tion filters are coevolved. Parasite filters survive by generating result images similar
to original. Images survive by making the parasite filter results visible. A number
of subtleties require attention such as setting thresholds that define similarity, the
elimination of do-nothing filters, adjusting the evolutionary rates of parasites versus
images, and the balancing of unary and binary operators to control high frequency
banding. He cites Ficici and Pollack (
1998
) and confirms observing
evolutionary cy-
cling
, where genotypes are rediscovered again and again, and
mediocre stable
states
where the coevolving populations exhibit constant change with little improvement.
Greenfield notes:
×
In all of the examples we have seen: (1) it required an extraordinary effort to design a popu-
lation to coevolve in conjunction with the population of visual art works being produced by
an underlying image generation system, and (2) it was difficult to find an evaluation scheme
that made artistic sense. Much of the problem with the latter arises as a consequence of
the fact that there is very little data available to suggest algorithms for evaluating aesthetic
fitness...It would be desirable to have better cognitive science arguments for justifying
measurements of aesthetic content.
In later sections we will survey some of the work in psychology and the nascent
field of neuroaesthetics that may contribute to computational aesthetic evaluation as
Greenfield suggests.
10.2.11.2 Niche Construction by Agents
As discussed in McCormack and Bown (
2009
) an environment can be thought of
as having both
properties
and
resources
. Properties are environmental conditions
such as temperature or pH, and resources are available consumables required by
