Session

Using Genetic Algorithms to Breed Killer Squirrels

Can a computer program truly surprise its creator?

In this highly unusual session, you'll get a high-level introduction to genetic algorithms as we look at a simple scenario involving training a virtual squirrel to find an acorn and return to its tree in a 2D world without being eaten by the neighborhood dog.

Not exactly a common business problem, but this code-free overview lets us explore the basics of genetic algorithms, representing potential solutions as genes, evolving solutions over time, the role of crossover and mutation, and the importance of a well-thought-out fitness function.

All of this will be done to see if a computer can evolve a gene capable of solving a specific problem (spoilers: it can), and see if a computer can find solutions its programmer didn't even think were possible.

This is an interesting combination of a talk on what genetic algorithms are as well as a discussion of the role of side projects. It is intended for a shorter time slot, but a longer abstract could be made for a more in-depth talk covering more technical details.

Matt Eland

Microsoft MVP & AI Specialist at Leading EDJE

Columbus, Ohio, United States

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