Ultimate Tic Tac Toe

Ultimate Tic-Tac-Toe is a modification of the traditional game of tic-tac-toe with a much more interesting ruleset. A full description of the rules can be found here. This repo is an older copy of my UTTT program which includes all the nasty stuff needed to import and run models built with Weka. This software is not terribly stable, especially under non-Linux operating systems and with non-Oracle JDKs.

This project includes:

A game engine for Ultimate Tic-Tac-Toe
An implementation of Monte Carlo Tree Search to play the game
Several models that attempt to score boards based on heuristics learned from recorded games
Dependencies and code to import and run Weka models
A tool for testing bots against other bots or human players

Installation

This project requires Python 3.5+, pip, and Oracle JDK 1.7+. On Linux, the JAVA_HOME variable must be set. On Windows, you may want to add python and pip to the system path.

Clone the repository:

$ git clone https://github.com/zachdj/ultimate-tic-tac-toe.git

Environment variables are stored in the settings.py file, which is ignored by default. Make a copy of the included settings.py.example file and rename it to settings.py. Open the file in a text editor and set any applicable variables.

Dependencies are managed using pipenv. Use pip to install pipenv:

$ pip install pipenv

Then cd to the project directory and install dependencies:

$ cd path/to/ultimate-tic-tac-toe
$ pipenv install

This will create a virtual environment for the project and install any required dependencies inside the virtual environment. Finally, activate the virtual environment and run the main.py file:

$ pipenv shell
$ python main.py

Usage

Using the GUI

Interacting with the program's graphical interface is straightforward. Games can be played/visualized by clicking the "Play Game" button from the main menu. Experiments (multiple games between bots) can be run from the "Run Experiment" menu. If the "Record Result" option is enabled, the board states and their win rates will be stored in a local database specified by the DB_LOCATION option in settings.py.

Development

Much of this codebase was developed as part of a class project for the course "CSCI 6550 - Intro to AI" at the University of Georgia in Fall 2017. If you're interested in contributing, you can contact me at zach.dean.jones@gmail.com.

License