Abstract: One hundred and fifty years have passed since the publication of Darwin’s world-changing manuscript “The Origins of Species by Means of Natural Selection”. Darwin’s ideas have proven their power to reach beyond the biology realm, and their ability to define a conceptual framework which allows us to model and understand complex systems. In the mid 1950s and 60s the efforts of a scattered group of engineers proved the benefits of adopting an evolutionary paradigm to solve complex real-world problems. In the 70s, the emerging presence of computers brought us a new collection of artificial evolution paradigms, among which genetic algorithms rapidly gained widespread adoption. Currently, the Internet has propitiated an exponential growth of information and computational resources that are clearly disrupting our perception and forcing us to reevaluate the boundaries between technology and social interaction. Darwin’s ideas can, once again, help us understand such disruptive change. In this talk, I will review the origin of artificial evolution ideas and techniques. I will also show how these techniques are, nowadays, helping to solve a wide range of applications, from life science problems to twitter puzzles, and how high performance computing can make Darwin ideas a routinary tool to help us model and understand complex systems.

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Interesting twist using Google Analytics to do site optimization. The interesting part is the shift of mentality. Instead of scratching your head going for the best, why not put a bunch out there and using as a row data for the next generation. Sounds familiar?

Yes, they will not mention it, but it heavily uses a simple evolutionary model. Using they words: you start with a basic set of variations, then you measure, oh you may want to try another set of variants based on the best ones. Yes, definitely evolutionary-based flavor. After going over the presentation, you will be wondering why they do not called interactive genetic algorithm? Well, I do not have the answer, but what I can say is that process can be modeled using an interactive genetic algorithm. The DISCUS project has shown that for the last five years. An introductory paper about how interactive genetic algorithms can help with such kind of modeling can be found here.

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