Monte Carlo Tic Tac Toe

Monte Carlo Tic Tac Toe is a Python implementation of the classic Tic Tac Toe game with a twist - it utilizes the Monte Carlo simulation algorithm to play against the player. The game offers a challenging and strategic experience, where the AI opponent makes decisions based on randomized simulations, providing an unpredictable and engaging gameplay.

Play against an AI opponent powered by the Monte Carlo simulation algorithm Simple and intuitive interface for easy gameplay. Option to choose between different difficulty levels. Customizable board size for added complexity. Detailed performance metrics for the AI opponent. change this tmrw.

Python 3.11.8

Clone the repository:

Run the game:

Follow the on-screen instructions to play against the AI opponent.

The player is represented by 'X' and the AI opponent by 'O'. The player makes the first move by selecting an empty cell on the board. The AI opponent utilizes the Monte Carlo simulation algorithm to select its move. The game continues until either the player or the AI opponent achieves three in a row, or the board is filled (resulting in a draw).

Author: Midhun Mukundan