Tic-Tac-Toe with Minimax and Alpha-Beta Pruning

Welcome to the Tic-Tac-Toe game implemented in C++ with Minimax algorithm and Alpha-Beta Pruning! This console-based game allows you to play against an AI opponent that uses the Minimax algorithm with Alpha-Beta Pruning to make optimal moves.

Table of Contents

• Tic-Tac-Toe with Minimax and Alpha-Beta Pruning
  • Table of Contents
  • Introduction
  • Getting Started
    • Prerequisites
    • Installation
  • How to Play
    • Player Moves
    • AI Moves
  • Game Features
    • Print Board
    • Check Win
    • Make Move
    • Minimax Algorithm
    • Alpha-Beta Pruning
  • Examples
  • Contributing
  • License

Introduction

This Tic-Tac-Toe game is implemented in C++ and features a simple console interface. The AI opponent is powered by the Minimax algorithm, a decision-making algorithm widely used in two-player games. The implementation also includes Alpha-Beta Pruning to optimize the search space and improve performance.

Getting Started

Prerequisites

Before running the game, ensure that you have a C++ compiler installed on your system.

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/MohammadrezaAmani/TicTocToe

2. Navigate to the project directory:

   cd TicTocToe

3. Compile the code using your C++ compiler:

   g++ -o tic_tac_toe main.cpp

4. Run the executable:

   ./tic_tac_toe

How to Play

Player Moves

• Enter your move by specifying the row and column (1-3) when prompted.

AI Moves

• The AI opponent uses the Minimax algorithm to make optimal moves.
• Watch out for strategic plays, as the AI aims to win or force a tie.

Game Features

Print Board

• The printBoard function displays the current state of the Tic-Tac-Toe board.

Check Win

• The checkWin function checks if a player has won the game.

Make Move

• The makeMove function allows players to make a move on the board.

Minimax Algorithm

• The minimax function implements the Minimax algorithm for decision-making.

Alpha-Beta Pruning

• The Minimax algorithm is enhanced with Alpha-Beta Pruning for improved efficiency.

Examples

Here's an example of how of using game:

int main()
{
    TicTacToe game;
    int currentPlayer = 1;

    while (true)
    {
        game.printBoard();

        if (currentPlayer == 1)
        {
            std::cout << "Player 1, enter your move (row and column): ";
            int row, col;
            std::cin >> row >> col;

            if (game.makeMove(row - 1, col - 1, currentPlayer))
            {
                if (game.checkWin(currentPlayer))
                {
                    game.printBoard();
                    std::cout << "Player 1 wins!" << std::endl;
                    break;
                }
                else if (game.isBoardFull())
                {
                    game.printBoard();
                    std::cout << "It's a tie!" << std::endl;
                    break;
                }
            }
            else
            {
                std::cout << "Invalid move. Try again." << std::endl;
                continue;
            }
        }
        else
        {
            game.makeAIMove();

            if (game.checkWin(2))
            {
                game.printBoard();
                std::cout << "AI wins!" << std::endl;
                break;
            }
            else if (game.isBoardFull())
            {
                game.printBoard();
                std::cout << "It's a tie!" << std::endl;
                break;
            }
        }

        currentPlayer = (currentPlayer == 1) ? 2 : 1;
    }

    return 0;
}

Follow the on-screen instructions to make your moves and enjoy the game!

Contributing

Contributions are welcome! If you have ideas for improvements or find any issues, please open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.