The purpose of this site is to provide an informative introduction to Genetic Algorithms: what they are,
how they work, who pioneered the field, what kind of problems these algorithms can solve, and current
applications of these algorithms. There even is an interactive example of a simplified Genetic Algorithm,
which attempts to reformat a picture to 32 colors while maximizing the picture quality, that can be found
here. Look to the toolbar on the right to find out more about
Genetic Algorithms: An Introduction
Our generation lives in a world filled with technology, so much so that we take most of it for granted.
We depend on everything from the most basic electronics that light our houses, to complex personal computers
that have almost become essential to this generation's well-being; these computers function as everything
from word processors to entertainment to our connection to the rest of the world. Despite the
growing power computers can be endowed with, able to surpass even the greatest human minds (Garry Kasparov,
the reigning chess champion at the time, was defeated by Deep Blue in 1997), society still believes in a
fundamental distinction between the intellegence of humans and of machines. We believe that machines don't have
the ability to truly think, to come up with creative solutions to new problems. However, a computer running a
Genetic Algorithm can find solutions to complex problems more effective than the best human scientists
can come up with, blurring the line between true and artifical intellegence.