Envision-TicTacToe-Bot

Tic Tac Toe is one of the most played games. The game is played by two players, who take turns marking the spaces in a three-by-three grid with ‘X’ (crosses) and ‘O’ (noughts). The player who succeeds in placing three of their marks consecutively in one column, row or diagonal is the winner. If both players play the best moves, the game ends in a draw.

This project aims to make two different types of bots to play this game. One of the types will be hardcoded. We will make agents that select their moves randomly, after considering moves to a depth of one, after considering moves to a depth of two and using the minimax algorithm. We will measure and compare success rates between these four agents, and a few games against a human.

The second type of bot will be a self-learning bot, which will learn how to optimize its playing style to make the best moves. We will not require to hard-code any instructions as to how to choose the next move. The model will play against another coded bot in order to learn what the best moves are, and improve itself.

Contributing Guidelines

Setting Up

• Fork the repository.
• Clone the forked repo using git clone <repo-url> to desired directory.

Pull Requests

• For each new submission, fix or feature create a new branch named <github-handle>-<explanatory-name>.

  git branch <branch-name>

• Switch to the new branch.

  git checkout <branch-name>

• Make the changes in the new branch.
• Stage the changes for the next commit. To stage changes from specific files:

  git add <filename>

  To stage all the changes at once:

  git add .

  Use git status to track the changes made.
• Commit the changes.

  git commit -m "<commit-message>"

• Push the changes to your forked repo. If you're working on a new branch:

  git push -u origin <branch-name>

  If the branch already exists:

  git push

• Create a pull request.

Keep in Mind

• Use meaningful small commits. Refer to this link.
• Remember to fetch changes from the upstream repo before working on something.

Resources

• General Machine Learning - You need not got through all of this and there is no special need to do these assignments.
• Reinforcement Learning course - This course is a must for understanding the basics of Reinforcement Learning.
• Useful subtopics - Make sure to read the articles once you feel you have a good understanding of ML.
• Game Theory - This course is optional, but is a very good resource to get into Game Dev, some of which we will be using for this project.
• Existing implementations - This is a great resource for learning how to implement the TicTacToe game using RL.
• Minimax - Minimax implementation and explanation