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Using DDQN with TensorFlow to solve 2048 - Putney School Project Week Fall 2020

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TensorFlow2048

This was my project for Project Week Fall 2020 at The Putney School.

I'm using tf_agents to build a neural network using DDQN to solve the game 2048.

If you want to see an agent of mine in action, use visualisation.py. It's also a good place to start if you want to look around the code. I think it's pretty well commented.

env.py contains the game logic as a TensorFlow PyEnvironment.
agent.py is for creating and training agents.
pg_implementation.py is a graphical interface for 2048 playable by both humans and robots, implemented in pygame.
visualisaton.py uses pg_implementation.py to show agents playing the game.
data_plots.py can make nice plots of data collected during training.

You control the pygame interface like this:
Move with arrow keys or WASD.
Press r to restart.
Press b to turn the bot off and on.

This project depends on the following packages:

  • tensorflow
  • tf_agents
  • numpy
  • pygame (only pg_implementation.py)
  • matplotlib (only data_plots.py)
  • scipy (only data_plots.py)

Feel free to send me any questions at [email protected]

2048 was originally created by Gabriele Cirulli and can be found here.
This software is published under the MIT License, see LICENSE.txt.

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Using DDQN with TensorFlow to solve 2048 - Putney School Project Week Fall 2020

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