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
Implements neuro-evolution by combining a 3-layer neural network (2 input neurons sensing gap distance/height, 6 hidden neurons, 1 output neuron) with a genetic algorithm that performs selection, crossover, and mutation across generations. Built entirely in HTML5 using the Phaser game framework and Synaptic neural network library, with fitness calculated as distance traveled minus proximity to obstacles.
About flappybird-es
alirezamika/flappybird-es
An AI agent Learning to play Flappy Bird using Evolution Strategies and deep learning models.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work