xviniette/FlappyLearning

Program learning to play Flappy Bird by machine learning (Neuroevolution)

47
/ 100
Emerging

This program helps demonstrate how machine learning can tackle simple control tasks in games. It takes the game state (like the bird's position and upcoming pipes) and, through an evolutionary process, learns to output the optimal 'flap' or 'no flap' action. This is primarily for developers, educators, or students interested in seeing neuroevolution in action within a game context.

3,997 stars. No commits in the last 6 months.

Use this if you are a developer, educator, or student who wants to understand or demonstrate the basics of neuroevolution and how it can be applied to create AI for simple games.

Not ideal if you're looking for an advanced AI system for complex game environments or a ready-to-use solution for game development without understanding the underlying AI principles.

game-ai neuroevolution machine-learning-demonstration educational-tool ai-experimentation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

How are scores calculated?

Stars

3,997

Forks

499

Language

JavaScript

License

MIT

Category

flappy-bird-ai

Last pushed

Nov 23, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/xviniette/FlappyLearning"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.