Metadata-Version: 2.1
Name: jokettt
Version: 0.0.3
Summary: A Tic Tac Toe game developed by joke
Home-page: https://github.com/fpiantini/jokettt
Author: Francesco Piantini
Author-email: francesco.piantini@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Requires-Python: >=3.6
Description-Content-Type: text/markdown

# JokeTTT: a Tic Tac Toe game developed by joke

JokeTTT is a tic tac toe game developed just for fun and to learn Python and some concepts of machine learning.

## Project setup

The project has been tested only with python3 on Ubuntu Linux. If you have python3 installed in your machine, just try the code entering the command:

```bash
./play.py
```

To avoid the usual problems with messy Python configurations (python 2 vs. 3, packages to install, etc.), conda is used for development.

For those that wants to do the same and does not know conda, this is a a quick reference:

- [TDHopper article on python environment with conda]
- [Get your computer ready for machine learning using *conda]

If you have conda installed, enter the project directory (the one with the environment.yml file) and enter the following command:

```bash
conda env create
```

This shall be done only the one time. After this the ```jokettt``` conda environment is created. It can be activated with the command:

```bash
conda activate jokettt
```

To update the conda environment every time that the ```environment.yml``` is changed, enter the command:

```bash
conda env update
```

## Credits

- A.L. Aradhya [Minimax introduction article] (and all the following) in geeksforgeeks.org for implementation of the minimax player
- T. Simonini "[An introduction to reinforcement learning]" for introduction theory on value function and for directing me to the Sutton and Barto book.

[TDHopper article on python environment with conda]: https://tdhopper.com/blog/my-python-environment-workflow-with-conda/
[Get your computer ready for machine learning using *conda]: https://towardsdatascience.com/get-your-computer-ready-for-machine-learning-how-what-and-why-you-should-use-anaconda-miniconda-d213444f36d6
[Minimax introduction article]: https://www.geeksforgeeks.org/minimax-algorithm-in-game-theory-set-1-introduction/
[An introduction to reinforcement learning]: https://medium.com/free-code-camp/an-introduction-to-reinforcement-learning-4339519de419


