# ssusnic/Machine-Learning-Flappy-Bird

Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm

Repository: https://github.com/ssusnic/Machine-Learning-Flappy-Bird
Canonical: https://ross.abutalabs.com/products/machine-learning-flappy-bird
Homepage: http://www.askforgametask.com/tutorial/machine-learning-algorithm-flappy-bird
Language: JavaScript
License: MIT
License Family: permissive
Topics: machine-learning, flappy-bird, genetic-algorithm, machine-learning-algorithm, artificial-intelligence, neuroevolution, ai-tutorial, ai, artificial-evolution, game-programming, html5, javascript, phaser, phaser-tutorial, machinelearning, machine-intelligence, neural-networks, neural-network, genetic-algorithms, flappybird
Last push: 2017-12-19T10:22:15+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3310, "days_push": 3179, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1839, forks 392 (observed 2026-08-28T04:05:42.920183+00:00)

## What it is
An HTML5 tutorial project that teaches an AI to play Flappy Bird using a neural network trained via a genetic algorithm (neuroevolution). It is built with the Phaser game framework and the Synaptic neural network library, with a full write-up and live demo.

## Use cases
- learn neuroevolution by example
- see a genetic algorithm train a neural network
- build an AI game controller in JavaScript
- teach machine learning concepts with a game demo
- starting point for AI-plays-game projects in Phaser

## When to choose
- learning how genetic algorithms and neural networks combine
- wanting a small, readable JavaScript ML demo
- building a similar AI-plays-game tutorial project

## When to avoid
- need a production ML framework or library
- want actively maintained code (last release 2017)
- need supervised or deep learning training pipelines

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, game, simulation, deep-learning
- domain: artificial-intelligence, machine-learning, tutorials, education
- platform: browser
- tags: neuroevolution, genetic-algorithm, neural-network, flappy-bird, phaser, synaptic, html5-game, ai-tutorial, game-development, javascript, html5

## Member repositories
- ssusnic/Machine-Learning-Flappy-Bird (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:42.920183+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 2026-08-30T03:18:15.387520+00:00, confidence not recorded.
  - readme: https://github.com/ssusnic/Machine-Learning-Flappy-Bird (fetched 2026-08-28T04:05:42.920183+00:00, sha 32bccf4b88a8)
  - homepage: http://www.askforgametask.com/tutorial/machine-learning-algorithm-flappy-bird (fetched 2026-08-29T10:57:28.740082+00:00, sha c9a7aa52b9a1)
  - site_page: https://www.askforgametask.com/about (fetched 2026-08-29T10:57:28.750625+00:00, sha f3a790a4a43f)
- Data as of 2026-08-30T08:39:29.467469+00:00.