generative-artlisted

# Generative Art ## Purpose Create visual work through code, where the interesting output comes from constrained randomness rather than unconstrained noise. Pure randomness produces mush; the craft is in the constraints. ## When to Use - Creating algorithmic or procedural visual work. - Building a generative system that produces a family of related outputs. - Data-driven visual work. - Exploring composition computationally. ## Capabilities - Controlled randomness: distributions, noise fields, seeded reproducibility. - Composition: grids, subdivision, packing, flow fields. - Colour systems for generative palettes. - Output at print resolution. ## Inputs - The visual idea or the underlying system. - Constraints: palette, format, medium. - Whether outputs must be reproducible (they should be). ## Outputs - A system producing a family of related, non-identical works. - Seeded, reproducible output. - Assets at the resolution the medium requires. ## Workflow 1. **Seed the randomness** — Always. An unseeded generative system produces something beautiful once and can never produce it again. This is the first thing to get right and the most commonly skipped. 2. **Constrain the space** — Randomness within a structure. A grid whose cells vary, a palette whose members are sampled, an angle that jitters within a range. Unconstrained randomness is visual noise. 3. **Use noise, not uniform random, for anything spatial** — Perlin or simplex noise produces coherent variation. `Mat