Idea Network: Divergent-Convergent Brainstorming Simulator

Divergent Thinking

Click "Spawn Idea" to branch a new idea off an existing one.

Network Physics

Association strength (springs) 40

Idea repulsion 55

Damping 0.90

Convergent Thinking

Solution clusters (k) 3

Session Stats

Ideas

Connections

Avg. novelty

0.0

Mode

Diverging

How it works

Each idea is a node in a force-directed graph. Two forces act on every node every frame:

Spring (Hooke's law, along each connection):
  F_spring = -k * (d - d0) * dir(i to j)

Repulsion (Coulomb-style, every pair of ideas):
  F_repel = C / d^2 * dir(away from j)

v += (F_spring + F_repel) * dt;  v *= damping
p += v * dt

Divergent phase: "Spawn Idea" attaches a new node to a random existing idea with a spring rest-length set by the chosen SCAMPER technique (Substitute, Combine, Adapt, Modify, Put-to-other-use, Eliminate, Reverse) — a standard structured-ideation checklist. Repulsion keeps ideas from collapsing onto each other, so the network fans outward exactly like a real brainstorm branching into sub-ideas.

Convergent phase: "Converge Ideas" runs Lloyd's algorithm (k-means): every few frames each idea is assigned to its nearest of k moving centroids, then an extra spring pulls it toward that centroid. Centroids relocate to the mean position of their assigned ideas. Repeating this assignment-then-relocation loop is exactly how design-thinking workshops group scattered ideas into a handful of solution clusters after a divergent brainstorm — the double-diamond "diverge, then converge" pattern.

Novelty is each idea's Euclidean distance from the network's centroid — ideas pushed far out by repulsion and long SCAMPER leaps read as more novel; converging pulls novelty back down as ideas settle into shared clusters.

Idea node Association (spring)

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