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Chrome-Dino-Reinforcement-Learning

A Deep Convolutional Neural Network to play Google Chrome's offline Dino Run game by learning action patterns from visual input using a model-less Reinforcement Learning Algorithm

NOTE: This is a basic-implementation repository with some limitations. Please refer https://github.com/Paperspace/DinoRunTutorial where I've used a GPU VM for better results, with scores upto 4000

Refer the jupyter notebook for detailed implementation :
https://github.com/ravi72munde/Chrome-Dino-Reinforcement-Learning/blob/master/Reinforcement%20Learning%20Dino%20Run.ipynb

Installation

Start by cloning the repository

$ git clone https://github.com/ravi72munde/Chrome-Dino-Reinforcement-Learning.git
Dependencies can be installed using pip install or conda install for Anaconda environment

Dependencies

  • Python 3.6
  • Selenium
  • OpenCV
  • PIL
  • Keras
  • Chromium driver for Selenium

gif

Sample Game Play

https://youtu.be/0oOOqGFmlDs

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An RL implementation in Keras

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  • CSS 1.2%
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