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flappybird-ai's Introduction

Learning to Flap using RL techniques

Implementations:

  • Simple Q-Learning
  • Q-Learning (with ε-greedy policy)
  • Deep Q-Network

Presentation:

This set of slides present our work in a concise way. You might want to check it out.

Blog:

A more detailed account about this project have been documented on this blogpost here.

Installation Dependencies:

  • Python 3
  • pygame
  • scikit-image
  • Keras 2

Simple Q-Learning:

Running the saved model:

python flappy_rl.py Run

Training the model:

python flappy_rl.py Train

To train a fresh model, delete the file qvalues.txt before executing the above command.

Q-Learning (with ε-greedy policy):

Running the saved model:

python flappy_rl.py Run greedy

Training the model:

python flappy_rl.py Train greedy

To train a fresh model, delete the file qvalues_greedy.txt and then execute the above command.

Deep Q-Network (DQN):

Running the saved model:

python dqn.py Run

Training the model:

python dqn.py Train

To train a fresh model, delete the file dqn.h5 and then execute the above command.

Raw Environment:

https://github.com/sourabhv/FlapPyBird

flappybird-ai's People

Contributors

sumanvid97 avatar

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