Primary: The Flame Algorithm and its Open Source Culture
Secondary: Artificial evolution for computer graphics
Eric Fairbanks
Literature Review #1
Karl Sims’ article “Artificial evolution for computer graphics” discusses the
generation of graphical content by use of natural selection on semi-randomly
parameterized algorithms. It describes how systems of evolution can be applied to image
and animation formation in combination with human feedback in order to generate
content that is aesthetically pleasing.
The article explains the difference between genotypes and phenotypes, and that by
taking a genotype (for instance, a lisp expression that generates graphical content) that is
known to produce appropriate phenotypes (content), and applying small amounts of
randomization to it, new genotypes can be creates that spawn similarly appropriate
phenotypes. A process of natural selection can be applied to these in order to weed out
undesirables, and the successors can be used to spawn further desirable genotypes.
Further, the article discusses how genotypes can be “mated.” Two algorithms or
parameter sets with desirable characteristics can be combined in a number of different
ways in order to generate new genotypes. This can be done by either swapping out
parameters, one for the other, or by linearly interpolating between parameters. Both offer
the potential to generate a large number of new genotypes with characteristics similar to
their parents.
The article concludes that genetic mutation and natural selection are viable
strategies for creating software that generates visually pleasing content. This theory is
reinforced by “The Flame Algorithm and its Open Source Culture” by Scott Draves and
Isabel Walcott Draves, which gives a brief history of the iconic Flame algorithm and
explains how it has impacted society and modern culture.
The Flame algorithm is a perfect example of an algorithm that lends itself
naturally to evolution. It is the combination of multiple fractal generation algorithms
combined to create a complex, multidimensional, virtual structure. These structures, as
the article explained, are easily identifiable and tend to be aesthetically pleasing. As such,
they have been featured in artwork ranging for movies, to music videos, to magazine
covers.
Scott Draves himself is the creator of the popular Electric Sheep screen saver, a
shining example of the sort of human-feedback-based, evolutionary graphics algorithm
that is described in “Artificial evolution for computer graphics.” Electric sheep has a
system that allows users to tweak or randomize parameters without requiring them to
understand the underlying system that generates the content. From this, Flame generation
algorithms, or “Electric Sheep,” are created.
These sheep are selected for desirable traits, stored in an online database, and bred
and morphed by a system that the user is neither required to see nor use. The parameters
sets, or genomes, are interpolated and meshed together in real time, so that the
screensaver, while actually a large, sequential set of mixed genomes, appears to be one
fluid, multidimensional fractal. The results are stunning.
Electric Sheep is an excellent example of the sort of software outlined in
“Artificial evolution for computer graphics.” It takes the concepts contained in the article
and applies them in an interesting and practical manner. Most importantly, it was a
success. Users were happy to use the program without understanding its inner workings,
simply because it generated content that, by its very nature and by their participation,
appealed to them.