Music Theory, Genetic Algorithms, & Python

Nov 23, 2017 · London, United Kingdom

We're extremely lucky to have Nicholas Tollervey leading a session combining music theory, genetic algorithms and python.

Genetic Algorithms

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?

Here's Google's experiment to teach a computer to accompany your own playing.

Fun Project & Challenge

Nicholas will present a fun project that uses genetic algorithms to discover solutions for contrapuntal musical exercises. On the way we'll geek-out over musical theory, explore how genetic algorithms work and pose a musical Turing-test.

Will you be able to tell the difference between computer generated counterpoint and that composed by a human?

Practical Stuff

The session will start at 7pm, you can arrive from 6.30pm.

Please also sign up on the skills-matter page [link].

Event organizers
  • Algorithmic Art

    Algorithmic Art is about maths and code making art. Our community is a diverse friendly place to share ideas, be inspired by each other, show what we're working on, support each other with coding, and discuss what our art means to us. We hope to inspire artists to learn to code, technologists to explore art, and first time coders to get started in fun way that stimulates the senses.  Over the last year we've covered themes as diverse as robotics, natural language processing, ray tracing, computer genera

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