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Vaniver comments on AlphaGo versus Lee Sedol - Less Wrong Discussion
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Sure, you can model music composition as a RL task. The AI composes a song, then predicts how much a human will like it. It then tries to produce songs that are more and more likely to be liked.
Another interesting thing that alphago did, was start by predicting what moves a human would make. Then it switched to reinforcement learning. So for a music AI, you would start with one that can predict the next note in a song. Then you switch to RL, and adjust it's predictions so that it is more likely to produce songs humans like, and less likely to produce ones we don't like.
However automated composition is something that a lot of people have experimented with before. So far there is nothing that works really well.
Emily Howell?
I was thinking more like these examples:
https://ericye16.com/music-rnn/
http://www.hexahedria.com/2015/08/03/composing-music-with-recurrent-neural-networks/
https://www.youtube.com/watch?v=0VTI1BBLydE
https://highnoongmt.wordpress.com/2015/05/22/lisls-stis-recurrent-neural-networks-for-folk-music-generation/
I think what Vaniver means is: It seems that Emily Howell works pretty damn well, contrary to your claim that nothing does. (By, so far as I understand, means very different from any sort of neural network.)
I know the conversation here has run its course, but I just wanted to add: whether or not Emily Howell is seen as something that "works really well" as an automated system is probably up for debate. It seems to require quite a bit of input from Cope himself in order to come up with sensible, interesting music. For example, one of the most popular pieces from Emily Howell is this fugue: https://www.youtube.com/watch?v=jLR-_c_uCwI - we really don't know how much influence Cope had in creating this piece of music, because the process of composition was not transparent at all.