Machine-Learning-Flappy-Bird and flappybird-es
Both projects are independent implementations of evolutionary AI approaches to Flappy Bird (one using genetic algorithms, the other evolution strategies), making them **competitors** that explore similar machine learning paradigms applied to the same game environment.
About Machine-Learning-Flappy-Bird
ssusnic/Machine-Learning-Flappy-Bird
Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm
This project helps game developers and AI enthusiasts explore how machine learning can be applied to simple game environments. It demonstrates how a 'bird' character can learn to navigate obstacles in a Flappy Bird-style game. By inputting the bird's distance and height relative to gaps, the system outputs optimal flap actions, allowing users to see an AI agent learn to play the game.
About flappybird-es
alirezamika/flappybird-es
An AI agent Learning to play Flappy Bird using Evolution Strategies and deep learning models.
This project showcases an AI agent that learns to play the game Flappy Bird. It takes the game's visual information as input and outputs actions (flapping or not) to navigate the bird through pipes. Anyone interested in observing how an AI can master simple video games through simulated evolution would find this engaging.
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