We’ve heard albums made by singular compositional minds and by bands. What would an album sound like if composed by swarm intelligence, by computer evolutionary models of individual agents or bots? That’s the question asked by composer Evan Merz in his new, full-length album “Black Allegheny.” (At top: the composer explains in a video.)
Western musical and creative tradition is steeped in linearity, from the forward motion of the music staff to the mythos of Aristotle’s Poetics.
So, maybe it’s little wonder that generative music – music that may not have linearity, or a beginning, middle, and end – hasn’t exactly been a big hit with the kids. Pioneers like Brian Eno have helped spread the gospel of generative music, but apart from lots of interesting experiments, there hasn’t been a lot of actual musical content. If you were to make a stack of generative music albums, your listening list would be fairly short.
All of that could be about to change. Programming code, the essential medium in which such models can be developed, is more accessible than ever. It’s also more visual, thanks to the popularization of tools like Processing, which can help make the abstract rules of generative music easier to grok. Merz, for his part, has taken on the challenge with his own Java-based software.
Saying the bots “compose” the music may be a little misleading. Generative music needs rules to operate. Before Eno, there was John Cage, whose “chance” compositions were as much defined by choices of materials as by ranges of indeterminacy. Merz makes a nod to Cage’s notion of a “gamut,” a collection of raw musical elements used as the input in the chance system. Here, though, Merz is aided by something Cage didn’t have: a swarm of intelligent “agents” can navigate those materials via simple rules, giving the music form and substance. Because they aren’t aware of the big picture, the music evolves more naturally, rather than being subjected to an over-arching narrative.
Or, as Merz puts it, “the tiny ant on the ground knows only what it sees around it.”
So, that’s the theory — what does the music sound like? Far from “ennui,” as Merz puts it, to me the results are organic. The structure is emergent from its materials, sounding almost like a natural physical process, like watching ice melt. The content ranges based on the gamut; like a lot of generative music, some sounds a whole lot like Brian Eno’s work. Others borrow from minimalist composers (Reich’s music itself might be seen as partially generative), and others take on an edgy urgency. The models that determine the bots are based on a popular, simple mathematical predator/food model, one often used in these works. Sometimes, you might imagine that evolutionary struggle playing out in the music.
You can read more about the process of developing this tool and the compositional ideas behind it at Evan’s blog:
Black Allegheny, Swarm Generated Music [Computer Music Blog]
For more explorations of sound and composition, check out Noise for Airports, which recently featured the work:
And you can stream the album or buy it for yourself for the light price of US$5 — though I’d like to see a software release, since that would mean each playback could be different. (Eno released an album in software form in the 90s, though tracking down the software now is evidently impossible – anyone with tips?)
Black Allegheny @ Bandcamp [Stream / download purchase]