Tic-Tac-Toe AI using Minimax Algorithm

This project implements a Tic-Tac-Toe game where you can play against an AI that uses the Minimax algorithm to make optimal moves.

Project Structure

• tictactoe.py: Contains the game logic and implementations for various functions required to play Tic-Tac-Toe.

• runner.py: Provides the graphical interface to play the game against the implemented AI.

• requirements.txt: Lists the Python dependencies required for this project.

Getting Started

USE PYTHON3 AND PIP3 WHILE USING ON MACOS OR LINUX

1. Clone this repository: git clone https://github.com/naman39/projects/tree/main/tictactoe
2. Change the directory to the repo directory cd <repository-directory>
3. Install dependencies: pip install -r requirements.txt
4. Run the game: python runner.py

Gameplay Instructions

• The game starts with X making the first move.
• You can make your move by clicking on an empty cell in the graphical interface.
• The AI will then make its move based on the Minimax algorithm.
• The game ends when either a player wins or the board is full (tie game).

Functions Implemented

• player(board): Determines whose turn it is (X or O).
• actions(board): Returns all possible legal moves for the current player.
• result(board, action): Returns the board that results from making a move.
• winner(board): Determines the winner of the game, if any.
• terminal(board): Checks if the game is over (terminal state).
• utility(board): Returns the utility of the current board from the perspective of the player.

Minimax Algorithm

• The AI uses the Minimax algorithm to ensure it plays optimally:

• Minimax is a recursive algorithm that considers all possible future moves to choose the best one.

• It assumes that both players play optimally, thus aiming to minimize the maximum possible loss (minimize the opponent's best possible outcome).