Choice of generative systems

We have previously seen I have made a personal approach that fits my needs. I am after autonomous evolution of patterns and would then rather use iterative, computational, processes such as cellular automata.

From generalization to specific choices

A generative system is a technique that builds information or material in an autonomous way, without human intervention. The question of autonomy is relative because it totally depends on where, in the creative process, control is done, or whether it should just exist. This existential question does not totally define what a generative piece is but its consequence nevertheless defines its outcome. Such system is often automatic and allows multiple versions following the same initial concept. The definition of how the automation should performed is often detailed by algorithms in which there exists a full scale of arbitration between randomness and predictability, both for the outcome and the making.

The necessity for formalization is then questioned. My experience, alongside the tools I am offered, revealed to me the necessity to choose the right balance between generalization and specification for a generative system.

Generative systems are technologies with the overall capacity to produce un-prompted change driven by large, varied, and uncoordinated audiences. When generative systems provide a common platform, changes may occur in varying layers (physical, network, application, content) and provide a means through which different firms and individuals may cooperate indirectly and contribute to innovation.

Generative art refers to art that in whole or in part has been created with the use of an autonomous system. An autonomous system in this context is generally one that is non-human and can independently determine features of an artwork that would otherwise require decisions made directly by the artist. In some cases the human creator may claim that the generative system represents their own artistic idea, and in others that the system takes on the role of the creator.

An absolute generalization or total randomness, from a certain point of view only, would totally discredit the piece. I am dealing with a simple but true fact, the art of change, veränderungsgrad as Karlheinz Stockhausen would call it (Stockhausen et al.,1955). This option is primary in my choice for a generative system (1.3.3).

fig. 1.43 - Snapshot of the video Proxima b1 using a personal derivative of cellular automata.

It has a strong taste of computer arts from the 1980s.

fig. 1.44 - Another snapshot of the video Proxima b1 a few frames later. The piece normally uses three 4k screens in parallel; I use GPU power and Max Jitter jit.gen to compute all the points.

Computational and iterative algorithm as an evolutionary generative system

The piece Proxima Centauri b, created in Taipei in December 2016 for the Taipei National Museum of Fine Arts is a good example (fig. 1.43&1.44). It is inspired by the inner and surreal contemplative rhythms of Weiner Herzog’s Aguirre, the Wrath of God. The piece simply uses a Conway’s game of life and reaction-diffusion to create long and quick evolutions. This emerging spatial and sonic composition initially come from the concept of cellular automata (Zuse, 1969;

Penrose et al.,2013). Patterns come from a particular grammar at microscopic scales and propagates into macroscopic ones. The current system spreads into two different times: the sequence of frames and the spatial evolution of pixels

within frames. This creates an artificial universe to be listened and watched:

“This view is centered on the idea that physical phenomena are best un-derstood in terms of digital information processing concepts. In its most ex-treme forms, it suggests that the universe is discrete, deterministic, finite, and evolves by simple computing rules. The central conceptual equation for this line of thought is:

complexity in nature = emergence in computation.”

Roger Penrose, Tommaso Bolognesi, A Computable Universe, (Penrose et al.,2013).

As for Fomalhaut , this work is intended to be seen as a framed painting watched from a wide angle. But it is also intended to be read as close as possible by looking at individual groups of pixels (1.2.3). The image must be presented onto several relatively small screens with the highest possible pixel density. The best version would again be with e-paper when the technology will be available.

Each screen starts with the same setup; the same initial pattern and a set of rules. Even after many iterations, they would get the same complex outcome until a point of randomness decided by one rule would radically change the evolution for each single screen.³² The system is not an actual game of life because I use additional time-based rules using delays and operations between layers. The strong aspect of recursion brings aliveness alongside its spatial and timed visual rhythm I am after. The sonic part strictly follows what is seen.

One can clearly hear recurrent swinged micro-loops. The sonic generation is then entirely build by the same cellular automata as the visual. I however had sometimes to select only one layer for clarity.

I also explored systems based on transformations from one state to another using a great deal of operators. Such procedures involve a series of agents conducted in a certain order. Form comes from information propagating inside a composition space. This clearly involves a synergy between iterations and computation. The model of computation is based on the repetition of a large amount of elementary processes. Computational design is here deeply involved because they provide composition tools which better suit conceptual and time-based approach rather a purely musical one.

Finite or parametric

Connections between continuous evolution and discrete states are done by the public himself, at the moment of interpretation (1.4.2). But the choice

be-32Aggregation is essential. I believe it models how my ideas propagates from random initial sparks to form (1.3.2).

tween finite states and a more parametric approach depends on the needs of the composition. Everything needing discrete elements like rhythms will need a finite approach. A continuous approach will more be dedicated for articulations and trajectories (1.3.2). It gets more subtle when actually connecting both ap-proaches together within a same composition process using various integrals.

This is the case with my piece Pictoris f . Depending on my needs, I use both approaches that sometimes get very close one form another.

fig. 1.45 - We can see in this future piece, certainly called Trappist-1 , that patterns are lying onto a quantum field. This piece has no intention of being linked with quantum mechanics;

just inspiration.

1.3.5 Transition

My core musical question correlates the relations and differences between classes of moments and positions. The simplest representation becomes an object for which each dimension corresponds to one composition parameter. This multi-dimensional body can be represented in a continuous parametric way from a specific scale. Mapping choices with synthesis parameters is primary, but scale sometimes defines continuity and allows iterative positioning resulting in the construction of patterns and forms. Computation with discrete elements never-theless generates complex displacements that can easily be arduous to compre-hend; although the concept can be beautiful, its artistic outcome often remains difficult. I adopted a perceptive approach where correlation between elements, giving a notion of time, is achieved using interference: moirés. I then focus on layers of waves and generate contrapuntal rhythmic layers. This strong

deci-sion implies a particular workflow and a way to deal with information from its generation to the manner in which it can be received.