Machine-Learning-Flappy-Bird and NeuroEvolution-Flappy-Bird
These are competitors—both implement AI approaches to play Flappy Bird (genetic algorithms/neuroevolution vs. neural networks), targeting the same use case of demonstrating machine learning techniques on a simple 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 NeuroEvolution-Flappy-Bird
ikergarcia1996/NeuroEvolution-Flappy-Bird
A comparison between humans, neuroevolution and multilayer perceptrons playing Flapy Bird implemented in Python
This project compares how well different AI methods, specifically neuroevolution and multilayer perceptrons, learn to play the game Flappy Bird. It takes in game state information like the bird's position and pipe distances, and outputs a decision to jump or not. This is for anyone interested in observing and understanding artificial intelligence learning in a game environment.
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