|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Flappy Es||140||a year ago||Python|
|Flappy Bird AI using Evolution Strategies|
|Flappy Bird Genetic Algorithms||75||6 years ago||2||mit||Python|
|Use genetic algorithms to train flappy bird|
|Flappybird Es||31||6 years ago||1||Python|
|An AI agent Learning to play Flappy Bird using Evolution Strategies and deep learning models.|
|🥕 Mastering flappy bird with machine learning (neural networks, neuro-evolution)|
This AI agent uses Evolutional Strategies and deep learning models to master the Flappy Bird game.
Read Evolution Strategies as a Scalable Alternative to Reinforcement Learning from OpenAI if you are interested.
After a few hundred iterations, it masters the game.
To see the agent playing the game:
from flappy import * agent = Agent() # the pre-trained weights are saved into 'weights.pkl' which you can use. agent.load('weights.pkl') # play one episode agent.play(1)
To start training the agent:
# train for 100 iterations agent.train(100)