Library / Linear / Concavity & Diminishing Returns

Concavity & Diminishing Returns

Curved payoffs change optimal bets: diversify when concave, concentrate when convex.

convex: go bigconcave: diversify
shape dictates strategy · recreated schematic
INTERACTIVE LAB

Tolerance sandbox (original recreation)

happy 76% • avg. similar neighbors 49% • red ring = wants to move

LINEAR

When to use / misuse

Use → Portfolios, effort allocation, pricing tiers.

Difficulty → Core

REDCAPE → Design · Act

agent: concavity-checker
family: Linear
combine_with: [two other families]
rule: state failure mode before acting

Free sources: SFI Nonlinear Dynamics tutorial

← LibrarySee Playbook →
◍ Ask mentor about this →See REDCAPE playbook →

Attach to a lattice — combines with

Different families, shared jobs. Click to open alongside.

GAMES
Collective Action & Commons (Ostrom)
Shared pools survive with boundaries, monitors and graduated sanctions — no panacea.
SHARED JOBS: DESIGN · ACT
GAMES
Colonel Blotto
Split forces across fronts with no pure best move — win by being unpredictable.
SHARED JOBS: ACT · DESIGN
DECISIONS
Decision Trees + Value of Information
Fold back probabilities; pay for information only if it changes the action.
SHARED JOBS: ACT · DESIGN

More in Linear

Linear Regression
Best-fit line plus a causation audit. A big coefficient is not a big cause.
Categorical & Threshold Models
Buckets and cutoffs turn messy attributes into testable if-then rules.
← Linear RegressionCategorical & Threshold Models →