Evan X. Merz

Black Allegheny is a collection of pieces composed using swarm intelligence. Each piece in the album was assembled using custom software that tracks the motion of a virtual herd, and relates that information to pre-selected audio files. This software is called becoming, and it was born from an exploration of Cage's graph and gamut techniques. These techniques were expanded into the domain of digital audio, then swarm algorithms were added.

Becoming is an algorithmic composition program written in java, that builds upon some of John Cage's frequently employed compositional processes. Cage often used the idea of a "gamut" in his compositions. A gamut could be a collection of musical fragments, or a collection of sounds, or a collection of instruments. Often, he would arrange the gamut visually on a graph, then use that graph to piece together the final output of a piece. Early in his career, he often used a set of rules or equations to determine how the output would relate to the graph. Around 1949, during the composition of the piano concerto, he began using chance to decide how music would be assembled from the graph and gamut.

In Becoming, I directly borrow Cage's gamut and graph concepts; however, the software assembles music using concepts from the AI subfield of swarm intelligence. I place a number of agents on the graph and, rather than dictating their motions from a top-down rule-based approach, the music grows in a bottom-up fashion based on local decisions made by each agent. Each agent has preferences that determine their movement around the graph. These values dictate how likely the agent is to move toward food, how likely the agent is to move toward the swarm, and how likely the performer is to avoid the predator.

I wrote the score for this terrific toon by Mike Kalec and Ryan Kemp.

A demonstration of my virtual instrument based on geo-tagged calls from maphub.org

Now with nunchuk support, so you can be both a drummer AND a ninja!