We're extremely lucky to have Nicholas Tollervey (http://ntoll.org/about/) leading a session combining music theory, genetic algorithms and python.
Like several approaches to computer intelligence, genetic algorithms are inspired by how nature itself works. Just as natural selection and mutation allow species to evolve to solve emerging challenges, genetic algorithms evolve code to better solve challenges we might set. Here's the enthusiastic Daniel Shiffman's first of a video series introducing genetic algorithms.
"Can a computer compose musical counterpoint?"
Algorithms that generate art - whether visual or musical - must strike a delicate balance between being boringly predictable, and unbearably noisy and random. Interesting creations lie between these two extremes .. but can simple algorithms really create music that we'd enjoy listening to? Music that sounds like it came from the heart of a human, not the cold metal of a computer?
Fun Project & Challenge
Nicholas will present a fun project that uses genetic algorithms to discover solutions for contrapuntal (https://en.wikipedia.org/wiki/Contrapuntalmotion) musical exercises. On the way we'll geek-out over musical theory, explore how genetic algorithms work and pose a musical Turing-test (https://en.wikipedia.org/wiki/Turingtest).
Will you be able to tell the difference between computer generated counterpoint and that composed by a human?
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Music Theory, Genetic Algorithms, & Python
I am a classically trained musician, philosophy graduate, teacher, writer and software developer. I've been programming since 1984 when I taught myself by using my school's BBC B. I've been online since 1994 and made software development my career in 2002.