Dino Run

With 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

Installation

Start by cloning the repository

$ git clone https://github.com/Paperspace/DinoRunTutorial.git
You need to initialize the file system to save progress and resume from last step.
Invoke init_cache() for the first time to do this

Dependencies can be installed using pip install or conda install for Anaconda environment

• Python 3.6 Environment with ML libraries installed (numpy,pandas,keras,tensorflow etc)
• Selenium
• OpenCV

This project contains following files:

• run.py: Main Driver Code
• model.py: Neural network implementation (Model Architecture)
• model.h5: Trained & Saved model
• progress_viz.py: Visualize Training Progress
• chromedriver.exe: Chrome Driver for Windows