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.

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.

I'm pleased to announce the release of Disconnected, an album of algorithmic sound collages generated by pulling sounds from the web.

I prefer to call this album semi-algorithmic because some of the music is purely software-generated, while other pieces are a collaboration between the software and myself. Tracks four and six are purely algorithmic, while the other tracks are a mix of software-generated material and more traditionally composed material.

The software used in the sound collage pieces (1, 3, 4, 6) was inspired by Melissa Schilling's Small World Network Model of Cognitive Insight. Her theory essentially says that moments of cognitive insight, or creativity, occur whenever a connection is made between previously distantly related ideas. In graph theory, these types of connections are called bridges, and they have the effect of bringing entire neighborhoods of ideas closer together.

I applied Schilling's theory to sounds from freesound.org. My software searches for neighborhoods of sounds that are related by aural similarity and stores them in a graph of sounds. These sounds are then connected with more distant sounds via lexical connections from wordnik.com. These lexical connections are bridges, or moments of creativity. This process is detailed in the paper Composing with All Sound Using the FreeSound and Wordnik APIs.

Finally, these sound graphs must be activated to generate sound collages. I used a modified boids algorithm to allow a swarm to move over the sound graph. Sounds were triggered whenever the population on a vertex surpassed a threshold.

Disconnected is available for download from Xylem Records.

The Signal Culture Group just published The Signal Culture Cookbook. I contributed a chapter titled "The Mapping Problem", which deals with issues surrounding swarm intelligence in music and the arts. Swarm intelligence is a naturally non-human mode of intelligent behavior, so it presents some unique problems when being applied to the uniquely human behavior of creating art.

The Signal Culture Cookbook is a collection of techniques and creative practices employed by artists working in the field of media arts. Articles include real-time glitch video processing, direct laser animation on film, transforming your drawing into a fake computer, wi-fi mapping, alternative uses for piezo mics, visualizing earthquakes in real time and using swarm algorithms to compose new musical structures. There's even a great, humorous article on how to use offline technology for enhancing your online sentience – and more!

And here's a quote from the introduction to my chapter.

Some composers have explored the music that arises from mathematical functions, such as fractals. Composers such as myself have tried to use computers not just to imitate the human creative process, but also to simulate the possibility of inhuman creativity. This has involved employing models of intelligence and computation that aren't based on cognition, such as cellular automata, genetic algorithms and the topic of this article, swarm intelligence. The most difficult problem with using any of these systems in music is that they aren't inherently musical. In general, they are inherently unrelated to music. To write music using data from an arbitrary process, the composer must find a way of translating the non-musical data into musical data. The problem of mapping a process from one domain to work in an entirely unrelated domain is called the mapping problem. In this article, the problem is mapping from a virtual swarm to music, however, the problem applies in similar ways to algorithmic art in general. Some algorithms may be easily translated into one type of art or music, while other algorithms may require complex math for even basic art to emerge.

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