SORTING & PEER EFFECTS◉ LIVE LAB
Schelling Segregation
Mild individual preference for similar neighbors aggregates to stark city-wide segregation.
Use → Housing, schools, platforms. Try the tolerance sandbox below.
Core • Reason · Explain · Predict
AFTER SCOTT E. PAGE'S THE MODEL THINKER
Think in Models, Not in Stories.
One model is always wrong. A lattice of many — distributions, networks, diffusion, games, dynamics — turns raw data into judgment. Browse 38 of them and poke 11 live simulations.
38
MODELS
10
FAMILIES
11
LIVE LABS
7
REDCAPE JOBS
LIVE • SCHELLING LABOpen →
round 0 • happy 76% • avg. similar neighbors 49% • red ring = wants to move
DIFFUSION • SIRR₀ lab →
Same math: flu and pop-star fever
How the library works
01
Ask or browse
Start from a decision or a curiosity — forecasting, pricing, segregation, epidemics. The library is organized by job, not by math.
02
Tour the lattice
Open any model for the mechanism, the diagram, the misuse warnings, and a live lab. Then read its neighbors — wisdom lives between models.
03
Act hedged
Take 3–5 models to your problem, note where they disagree, and run the smallest test that could prove you wrong.
Seven jobs for models
Open the REDCAPE explorer →COMING SOON • AI MENTOR
A mentor that thinks in models.
- → Explains any of the 38 models in plain words
- → Reasons step by step, searches the web, and cites its sources
- → Recommends a lattice of models for your data — and where they disagree
In the workshopExplore the library meanwhile →
“I have weekly sales and ad spend — what should I use?”
→ Bass for the launch curve, regression for spend response, bandits for budget splits. Three models, one hedged plan.
10 families, 38 models
Full library →DISTRIBUTIONS • 5
The shape of outcomes: bells, long tails, rare counts, and how much surprise to expect.
Normal Distribution · Central Limit & Six Sigma · Power Law / Long Tail …
LINEAR & NONLINEAR • 3Lines, buckets, and bends — when effects add up, and when curvature flips the best move.
Linear Regression · Categorical & Threshold Models · Concavity & Diminishing Returns
SORTING & PEER EFFECTS • 3How individual thresholds and mild preferences aggregate into stark group patterns.
Schelling Segregation · Granovetter Threshold · Standing Ovation (Page–Miller)
NETWORKS • 3Who connects to whom — hubs, bridges, and the tipping point where islands fuse.
Network Structure & Formation · Preferential Attachment · Percolation / Tipping Points
DIFFUSION • 3How ideas, products, and germs spread: broadcast, word of mouth, and contagion.
Broadcast Model · SIR Contagion · Bass Diffusion (S-Curve)
DYNAMICS • 6Systems that move: noise, memoryless chains, path dependence, feedback, and equilibrium.
Random Walk & Markets · Markov Chain · Polya Urn / Path Dependence …
GROWTH • 2Compounding, capital, and ideas — why some economies and fortunes pull away.
Exponential & Solow Growth · Capital Share (r > g)
GAMES • 7Strategic interaction: dilemmas, coordination, signals, fair splits, and rule design.
Prisoner's Dilemma + Cooperation · Coordination & Culture · Colonel Blotto …
LEARNING • 4How populations and teams improve: replication, exploration, search, and diverse crowds.
Replicator Dynamics (Fisher) · Multi-Armed Bandit · Rugged Landscapes (NK) …
DECISIONS • 2Choosing under uncertainty, and how individual choices aggregate into group outcomes.
Decision Trees + Value of Information · Spatial Choice & Aggregation
Start with these four
DIFFUSION◉ LIVE LAB
SIR Contagion
Susceptible–Infected–Recovered with an R0 tipping point. Same math for flu and pop-star fever.
Use → Epidemics, memes, outages. Push R below 1 or segment the network.
Core • Explain · Predict · Act · Explore
DISTRIBUTIONS
Power Law / Long Tail
Rich-get-richer: a few huge winners, many tiny players. Straight line on log-log.
Use → City sizes, book sales, network degrees. Never average it like a normal.
Starter • Explain · Predict
LEARNING
Multi-Armed Bandit
Balance pulling the best-known lever against testing new ones. Regret is the score.
Use → Trials, dosing, ad creative. Run small experiments, then exploit.
Core • Act · Explore
Click any card — it opens as a modal with diagrams, explanations, and labs.
“To be wise you must arrange your experiences on a latticework of models.” — after Charlie Munger