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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Use this if you want to see how advanced AI techniques like neuroevolution can be applied to game playing and how they compare to simpler neural networks.
Not ideal if you're looking for a general-purpose game-playing AI or a tool to build your own game bots without understanding the underlying AI concepts.
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Jupyter Notebook
License
MIT
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Last pushed
Dec 28, 2017
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