Dear all, I'm trying to find reference to a story I read some time ago (a few years, perhaps?), and I'm hoping that either: a) I heard it from someone on this list, or b) someone on this list heard it, too.
Anyway, it was a really cool example of a real-world genetic algorithm, having to do with chickens. Traditionally, the best egg-producing chickens were allowed to produce the offspring for future generations. However, these new chickens rarely lived up to their potential. It was thought that maybe there were unknown things going on in the *clusters *of chickens, which represent the actual environment that these chickens are kept in. And that the high producers, when gathered together in these groups, somehow failed to produce as many eggs as expected. So researchers decided to apply the fitness function to *groups *of chickens, rather than individuals. This would perhaps account for social traits that are generally unknown, but may affect how many eggs were laid. In fact, the researchers didn't care what those traits are, only that - whatever they may be - they are preserved in future generations in a way that increased production. And the experiment worked. Groups of chickens that produced the most eggs were preserved, and subsequent generations were much more productive than with the traditional methods. Anyway, that's the story. If anyone can provide a link, I would be very grateful. (As I recall, it wasn't a technical paper, but rather a story in a more accessible venue. Perhaps the NY Times article, or something similar?) Thanks! -Ted
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