Machine-Learning-Flappy-Bird and flappy-es
These are ecosystem siblings—both implement different AI approaches (neural networks with genetic algorithms vs. evolution strategies) to solve the same Flappy Bird problem, representing alternative algorithmic implementations rather than tools designed to work together or replace each other.
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 flappy-es
mdibaiee/flappy-es
Flappy Bird AI using Evolution Strategies
This project offers an artificial intelligence model that learns to play the game Flappy Bird. It takes gameplay data as input and produces a trained AI that can expertly navigate the game. It is designed for AI researchers, game developers, or enthusiasts interested in applying evolutionary strategies to game challenges.
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