Evan X. Merz

In the past few days I've completed several programs that compose rather nice notated music using cellular automata. Yesterday I posted seven solos generated by cellular automata. Today I am following up with two duets. Like the solos, these pieces were generated using elementary cellular automata.

All of these pieces look rather naked. In the past I've added tempo, dynamics, and articulations to algorithmic pieces where the computer only generated pitches and durations. Lately I feel like it's best to present the performer with exactly what was generated, and leave the rest up to the performer. So these pieces are a bit more like sketches, in the sense that the performer will fill out some of the details.

Download the score for Two Duets Composed by Cellular Automata for any instruments by Evan X. Merz.

I've collected several pieces composed using cellular automata into one package.

This collection of seven solos for any instrument was created by computer programs that simulate cellular automata. A cellular automaton is a mathematical system containing many cellular units that change over time according to a predetermined rule set. The most famous cellular automaton is Conway's Game of Life. Cellular automata such as Conway's Game of Life and the ones used to compose these pieces are capable of generating complex patterns from a very small set of rules. These solos were created by mapping elementary cellular automata to music data. One automaton was mapped to pitch data and a second automaton was mapped to rhythm data. A unique rule set was crafted to generate unique patterns for each piece.

Download the score for Seven Solos Composed by Cellular Automata for any instrument by Evan X. Merz.

This is my synthesizer arrangement of Debussy's Prelude to the Afternoon of a Faun.

Isao Tomita did version with actual analog synthesizers in the 1970s.

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.

Donate to the Signal Culture Group to get the full book!

On October 4, I will be presenting at the 3rd Annual Workshop on Musical Metacreation. I will be presenting a paper on the ways that AI practitioners have used ad hoc methods in algorithmic music programs, and what that means for the field of computational creativity. The paper is titled Implications of Ad Hoc Artificial Intelligence in Music Composition.

This paper is an examination of several well-known applications of artificial intelligence in music generation. The algorithms in EMI, GenJam, WolframTones, and Swarm Music are examined in pursuit of ad hoc modifications. Based on these programs, it is clear that ad hoc modifications occur in most algorithmic music programs. We must keep this in mind when generalizing about computational creativity based on these programs. Ad hoc algorithms model a specific task, rather than a general creative algorithm. The musical metacreation discourse could benefit from the skepticism of the procedural content practitioners at AIIDE.

The workshop is taking place on the North Carolina State University campus in Raleigh, NC. Other presenters include Andie Sigler, Tom Stoll, Arne Eigenfeldt, and fellow NIU alumnus Tony Reimer.