TimHanewich/tetris-ai-mini
Training a neural network (AI) to play a very simplified game of 4x4 Tetris using Q-Learning.
This project helps demonstrate how to train an AI agent to play a very simplified 4x4 Tetris game using Q-Learning, a reinforcement learning technique. It takes game board states as input and outputs optimal moves the AI should make. Researchers and students exploring reinforcement learning or AI development would find this useful for understanding basic AI training principles.
No commits in the last 6 months.
Use this if you are a student or researcher wanting a simple, clear example of reinforcement learning in action to understand how an AI learns to make decisions in a game.
Not ideal if you are looking for a complex AI solution for real-world strategic games or a production-ready game AI.
Stars
8
Forks
1
Language
Python
License
MIT
Category
Last pushed
Dec 30, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/TimHanewich/tetris-ai-mini"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
crispy-chiken/YugiohAi
A Yugioh Ai Learning bot
RyanSaxe/mtg
State of the Art Magic: the Gathering Draft and DeckBuilder AI.
Ludeme/LudiiTutorials
This repository contains various tutorials for game design and programming with the Ludii...
pbondoer/leekwars
(simple) Leek Wars AI
KINGdotNET/kingdotnet.github.io
KING.NET - Free Games for Life.