Creative Innovation Simulation

Evolution Controls

Click any of the 9 forms below to mark it a parent (it gets a glowing ring). Then breed — children are recombined and mutated from your chosen parents. Pick none to mutate the whole population instead.

Mutation rate 15%

Novelty (macro-mutation) 8%

Population State

Generation

Parents chosen

0 / 9

Diversity

How it works

Each of the 9 forms is a genome — 8 numbers — decoded into a 3D mesh with the Gielis superformula, a single equation that generalises circles, stars, polygons and organic blobs into one continuous family:

r(θ) = ( |cos(mθ/4)/a|^n2 + |sin(mθ/4)/b|^n3 )^(-1/n1)

x = r(θ)·cosθ · r(φ)·cosφ
y = r(θ)·sinθ · r(φ)·cosφ
z = r(φ)·sinφ

Two independent superformula calls — one over longitude θ (gene m1), one over latitude φ (gene m2) — sculpt a closed 3D "supershape". A twist gene shears each latitude ring, and a texture gene adds a deterministic ripple to the radius, on top of shared shape exponents n1, n2, n3.

This is interactive evolutionary computation (IEC): instead of a fitness formula, you are the fitness function. Click the forms you find most interesting, then Breed — each child's genome is built by uniform crossover between two randomly-chosen parents from your selection, then each gene is nudged by Gaussian-like mutation at the rate you set. A Novelty slider adds a small chance of a fully random gene value, so the population doesn't converge and go stale.

No selection — the whole current population becomes the parent pool (gentle drift).
Diversity — average normalised gene-distance across all 9 genomes; it drops as the population converges on a look and jumps back up after a Randomize.

Real-world relevance: this is the same technique behind Richard Dawkins' "biomorphs", Karl Sims' evolved virtual creatures, and production tools like generative CAD and procedural game-asset pipelines, where a designer steers a search space too large to explore by hand.

Click a form to select it as a parent

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Creative Innovation Simulation: Evolving Forms with a Genetic Algorithm