# red42/HTML5_Genetic_Cars

A genetic algorithm car evolver in HTML5 canvas.

Repository: https://github.com/red42/HTML5_Genetic_Cars
Canonical: https://ross.abutalabs.com/products/html5_genetic_cars
Language: JavaScript
License: Zlib
License Family: permissive
Archived: true
Last push: 2026-03-13T12:14:52+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 72, release rhythm 35, longevity 100
- inputs: {"age_days": 4810, "days_push": 173, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1227, forks 306 (observed 2026-08-28T04:04:03.326849+00:00)

## What it is
A browser-based simulation that evolves 2D cars using a genetic algorithm rendered on HTML5 canvas with the Box2D physics engine. It runs entirely client-side with no build step, originally published as a web demo.

## Use cases
- evolve cars with a genetic algorithm in the browser
- demonstrate genetic algorithms to students
- visualize evolutionary optimization over generations
- explore physics-based fitness simulation
- teach evolutionary computation concepts interactively

## When to choose
- you want a zero-setup, browser-only demo of genetic algorithms
- you need an educational visualization of evolution and fitness over generations
- you want a lightweight physics-based evolution sandbox

## When to avoid
- you need a serious optimization or machine-learning framework
- you require headless large-scale evolutionary computation with programmatic APIs
- you need 3D simulation or real-world robotics control

## Facets
- artifact type: application
- maturity: maintenance
- function: simulation, game-engine, graphics, machine-learning
- domain: simulation, artificial-intelligence, education
- platform: browser
- tags: genetic-algorithm, evolutionary-computation, html5-canvas, box2d, physics-simulation, visualization, game-development, web-server

## Member repositories
- red42/HTML5_Genetic_Cars (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:03.326849+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:15:16.558928+00:00, confidence not recorded.
  - readme: https://github.com/red42/HTML5_Genetic_Cars (fetched 2026-08-28T04:04:03.326849+00:00, sha 482d50556bfa)
- Data as of 2026-08-30T08:39:29.467469+00:00.