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17-18-Reinforcement

How to play against the Agent

We have created a UI on a web page that one can run locally to play against the agent. Two agents were trained using the AlphaZero algorithm, one for a 15x15 board and one for a 10x10. The generated models were exported and are queried to make a move after each move made by the user. Both are available for play on the webpage. The 10x10 is stronger due to a decreased time needed to train it.

Dependencies

Python3, Flask, Keras, numpy, Theano, Tensorflow

Running

  1. Set the flask entrypoint to mod_main.py by using export FLASK_APP=mod_main.py
  2. Navigate to webapp/app
  3. Start the server with flask run

Team Members:

  • Shruti Alavala
  • Jared Gruneiro
  • Hannah Reed
  • Mya Rios
  • Parker Timmerman
  • Michael Wynne

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2017-18 Reinforcement Learning Senior Design Project

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