What are genetic algorithms?

Oh, genetic algorithms are FANTASTIC. I suppose you want more of an answer than that, though.

In brief, genetic algorithms are a way of posing a problem, any problem, as a "fitness solution", with a random set of possible solutions, or elements of possible solutions, being your "genome pool". These solutions then cycle through a set number of generations, being filtered so that those closest to the function you are after are given a "reproductive advantage" for the next iteration. Various genetic algorithms have different ways of weighting for reproductive advantage and different ways of introducing variation into each generation of possibles; different methods have different strengths and weaknesses.

To learn more about genetic algorithms, I suggest the following:

Intro presentation (warning -- contains some jargon):
http://lancet.mit.edu/~mbwall/presentations/IntroToGAs/

The first, best, and definitive FAQ:
http://www.cs.cmu.edu/Groups/AI/html/faqs/ai/genetic/top.html

The pretty good Wiki, including only a brief explanation but a good
section on applications and some more about genetic programming:
http://en.wikipedia.org/wiki/Genetic_algorithm

A little bit about genetic programming:
http://www.geneticprogramming.com/ (there's a link to a tutorial
first thing, too)

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