Art Collection Curator: Coherence & Value Simulator

Collection

Collection Value

Cash on Hand

Coherence Score

Wall Space

0 / 9

Auto-Curator

Curation focus Balanced

Market volatility Medium

Simulated time speed 1×/s = 1 mo

On the Market (pick to acquire)

How it works

Each candidate artwork is generated from a seed: a base hue h, a style, and a rarity r ∈ (0,1) drawn from a skewed distribution (rare pieces are uncommon: r = 1 − U², U~Uniform(0,1)). Its asking price is

price = 200 + 4000·r^1.8 · (1 + 0.4·styleFactor)

Owned pieces sit on the gallery wall as textured frames. The coherence score measures how well their dominant hues agree with a classic color-harmony scheme (analogous, ~±30°, or complementary, ~180°): for every pair of owned works the angular hue distance Δ is scored against the nearest harmonious angle, and the collection score is the mean of those pairwise scores. A single piece scores 100% by convention (nothing to clash with).

pairScore(Δ) = 100 · max(0, 1 − min(|Δ−30|,|Δ−180|)/60)
coherence   = mean(pairScore) over all owned pairs

Each simulated month, every owned piece appreciates or depreciates:

Δvalue = value · (0.006 + 0.02·rarity) · (1 + 0.5·coherenceBonus) + noise(volatility)

so rare pieces in a coherent collection compound value fastest, while a mismatched high-volatility collection can lose value. The curation focus slider blends two scores the auto-curator uses to rank market pieces before acquiring: aesthetic fit (how much a candidate would raise coherence) versus expected growth (rarity-driven appreciation potential) — 0% picks purely for fit, 100% purely for growth.

Year 0, Month 0 0 pieces owned

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