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Train an AI to play chess, and have your AI compete with other people's AIs! Named after https://github.com/ChesleyTan
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README.md

chessley-tan

Train an AI to play chess, and have your AI compete with other people's AIs! Named after https://github.com/ChesleyTan

About

This project was made for a Software Development class at Stuyvesant High School.

Upon making an account, users will be given a baby AI with almost no knowledge of chess other than the rules. Players will train the AI to improve its skills. Players will be ranked based on an ELO ranking system, gaining ELO points when their AI defeats another player's AI in a competitive match.

Libraries and APIs Used

  • Python Flask
  • TensorFlow
  • Python Chess
  • SciPy
  • Mongo
  • Sunfish

Sources

Hi, it's Ethan (elc1798). When I first started this project, I knew next to nothing about neural networks, machine learning, etc. A large portion of my knowledge came from reading research papers, the TensorFlow tutorial (https://www.tensorflow.org/versions/master/tutorials/index.html), and some open source neural net projects on GitHub. A large portion of the neural net in this project, named Chessley, is based on Erik Bernhardsson's Deep Pink: https://github.com/erikbern/deep-pink. I would also like to thank Keras's source code for helping me port Deep Pink's Theano framework to TensorFlow, where I made some modifications and tweaks (that probably contain some unintentional ones).

KERAS: https://github.com/fchollet/keras

Deep Pink Blog Post: http://erikbern.com/2014/11/29/deep-learning-for-chess/

Created by

Name Role
Ethan Cheng Deep Learning AI
Ishraq Bhuiyan Flask Web Application Backend
Jion Fairchild HTML and CSS Frontend

Building

Clone the project and build all dependencies:

$ git clone https://github.com/elc1798/chessley-tan
$ cd chessley-tan
$ make setup

To deploy the website, just do

$ gunicorn -w 4 -b 0.0.0.0:5000 wsgi_handler:app

To access the site, access your IP address or website on port 5000. The port can be changed to suit your needs.

Our version is hosted at http://vocab.csproject.org:5000

Video Demo

See: https://youtu.be/_JT_NjR5Ovw

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