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xviniette/FlappyLearning has 4,008 GitHub stars and 501 forks. GitHot measured +1 stars in 24 hours and +13 in 7 days. Last checked 2026-11-06 16:53 UTC. Last push 2023-11-23.

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Programme qui apprend à jouer à Flappy Bird grâce à l’apprentissage automatique (neuroévolution)

Progression mesurée des étoiles

in 24h
+1
in 7 days
+13
in 15 days
Historique en cours
in 1 month
Historique en cours

Variations nettes sur des périodes qui se chevauchent, pas des totaux quotidiens. Les mesures absentes restent vides. Les étoiles indiquent l’intérêt, pas la qualité.

README.md

Original

Flappy Learning (Demo)

Program that learns to play Flappy Bird by machine learning (Neuroevolution)

alt tag

NeuroEvolution.js : Utilization

// Initialize
var ne = new Neuroevolution({options});

//Default options values
var options = {
    network:[1, [1], 1],    // Perceptron structure
    population:50,          // Population by generation
    elitism:0.2,            // Best networks kepts unchanged for the next generation (rate)
    randomBehaviour:0.2,    // New random networks for the next generation (rate)
    mutationRate:0.1,       // Mutation rate on the weights of synapses
    mutationRange:0.5,      // Interval of the mutation changes on the synapse weight
    historic:0,             // Latest generations saved
    lowHistoric:false,      // Only save score (not the network)
    scoreSort:-1,           // Sort order (-1 = desc, 1 = asc)
    nbChild:1               // number of child by breeding
}

//Update options at any time
ne.set({options});

// Generate first or next generation
var generation = ne.nextGeneration();

//When an network is over -> save this score
ne.networkScore(generation[x], <score = 0>);

You can see the NeuroEvolution integration in Flappy Bird in Game.js.

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