# greerviau/SnakeAI

Train a Neural Network to play Snake using a Genetic Algorithm

Repository: https://github.com/greerviau/SnakeAI
Canonical: https://ross.abutalabs.com/products/snakeai
Language: Processing
License: MIT
License Family: permissive
Last push: 2023-11-17T12:00:53+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2862, "days_push": 1020, "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 2390, forks 556 (observed 2026-08-28T04:06:43.322410+00:00)

## What it is
A Processing application that trains neural networks to play the game Snake using a genetic algorithm with crossover and mutation across generations of 2000 snakes. It visualizes training progress, including best-score graphs per generation.

## Use cases
- train a neural network to play snake
- learn how genetic algorithms evolve neural networks
- demonstrate neuroevolution with crossover and mutation
- visualize fitness improvements across generations
- experiment with customizable neural network architectures
- educational demo of reinforcement-free learning

## When to choose
- you want a visual, self-contained demo of neuroevolution
- you are teaching or learning genetic algorithms and neural networks
- you want to run experiments with customizable network sizes in Processing

## When to avoid
- you need production-grade reinforcement learning with GPU acceleration
- you want a library to embed into your own projects rather than a standalone app
- you need Python or a modern ML framework ecosystem

## Facets
- artifact type: application
- maturity: maintenance
- function: machine-learning, simulation, game, data-visualization
- domain: artificial-intelligence, machine-learning, education
- platform: cross-platform
- tags: genetic-algorithm, neuroevolution, snake-game, processing, neural-network, evolutionary-computation, game-development, desktop

## Member repositories
- greerviau/SnakeAI (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:43.322410+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 2026-08-30T02:34:29.814963+00:00, confidence not recorded.
  - readme: https://github.com/greerviau/SnakeAI (fetched 2026-08-28T04:06:43.322410+00:00, sha 0b6a1a35b694)
- Data as of 2026-08-30T08:39:29.467469+00:00.