Evolution Lab Introductory 2 minute read Updated 2026-06-29 UTC

Population Simulator

How the browser-local population simulator teaches mutation, selection, diversity, carrying capacity, specialists, champions, and no-op outcomes.

Research statusBrowser-local tool guide Publication statePublished Reviewed byMichael Kappel Source reports3

Purpose

The Population Simulator makes model breeding visible. It turns mutation rate, selection pressure, carrying capacity, diversity, and retirement into a local experiment that can be run in the browser.

The point is not to predict a real model population. The point is to build intuition: too little variation stagnates; too little selection clutters; too little diversity creates a narrow ecology; a useful no-op preserves the current champion.

Controls to teach

ControlWhat it representsWhat visitors learn
Mutation rateHow far descendants move from parents.Variation must be large enough to explore but bounded enough to evaluate.
Selection pressureHow strongly evidence affects survival.Fitness evidence shapes the active population.
Carrying capacityHow many active artifacts the ecology can maintain.Frugal systems cannot keep everything active.
Specialist bonusReward for niche excellence.A narrow model can be valuable even if it is not a global winner.
Diversity bonusReward for coverage.Useful diversity prevents a single pattern from dominating every niche.
Release thresholdEvidence needed before active use.Release packets turn experiments into adoption-ready improvements.
Retirement thresholdValue needed to stay active.Retirement keeps the ecology lean while preserving lineage.

Suggested classroom exercise

Run the simulator three times: once with high mutation, once with high selection, once with high diversity. Compare the final champion, specialist count, and archived branches. Then ask which configuration better matches a legal assistant, a coding assistant, and a local telemetry assistant.

Toy ecology

Population pressure simulator

Run a deterministic toy model of mutation, scoring, diversity, no-op, and retirement. This is explanatory, not predictive.

Browser-local

Run the simulation to see the generation summary.

Source reports used for this guide

These reports are preserved verbatim in the site archive. The guide above is an editorial synthesis and may narrow, qualify, or reorganize claims from the source material.