AlphaGo has convolutional neural network, supervised learning, self-generated supervised learning, a mix-up strategy between Monte Carlo rollouts and goal function estimation. All these strategies are apted to go because it is a spatial game with a very well defined strategy function. While I do see CNN and supervised learning well worth of being used for music, it is much more difficult to come up with something that resembles the third step in AlphaGo: generating millions of random 'games' (simphonies) with their own label (good music/bad music) to train an 'intuitive' network.

I think the basic method could be applied to a more general engine like that of Zillions of Games. And having an engine that plays any kind of strategy game well would be astonishing.