Tic Tac Toe Kotlin

This repository contains a Tic Tac Toe game implemented in Kotlin, featuring a command-line interface (CLI) and an extensible AI system. The game supports customizable AI algorithms, with a default implementation of the Minimax algorithm.

Features

• Object-Oriented Design: The project uses Kotlin's enum class, data class, and inheritance to create a modular and extensible design.
• AI Support: The game includes a pluggable AI system, with Minimax as the default algorithm.
• Command-Line Interface: A simple and intuitive CLI for playing Tic Tac Toe.
• Extensibility: Easily add custom AI algorithms by extending the Algorithm abstract class.

How It Works

Game Components

• Mark: Represents the state of each cell in the game board (X, O, or BLANK).
• Position: Represents the coordinates of a cell on the board.
• Board: Manages the game state, including setting marks, checking for win conditions, and finding available moves.
• Algorithm: An abstract class for AI algorithms. Custom AI can be added by extending this class and implementing the play method.
• Minimax: The default AI algorithm using the Minimax strategy for optimal moves.

Board Functionality

• set(position: Position, mark: Mark): Marks a cell with X, O, or BLANK.
• get(position: Position): Mark: Retrieves the mark of a cell.
• checkWin(): Mark?: Checks if there's a winner and returns the winning mark, or null if there's no winner.
• getBlanks(): List<Position>: Returns a list of all available positions on the board.

AI Functionality

To implement a custom AI, extend the Algorithm class:

abstract class Algorithm {
    abstract fun play(board: Board, c: Mark): Position?
}

Example: Adding a new AI algorithm:

object CustomAI : Algorithm() {
    override fun play(board: Board, c: Mark): Position? {
        // Your custom logic here
    }
}

Installation

1. Clone the repository:

   git clone https://github.com/HadiAgdam/TicTacToeKotlin.git

2. Open the project in your favorite Kotlin IDE (e.g., IntelliJ IDEA).
3. Build and run the project.

How to Play

1. Run the application.
2. Choose whether you want to play as X or O.
3. Make your moves by entering the coordinates of the cell (e.g., 0 1 for the cell at row 0, column 1).
4. The AI will make its moves automatically.

Minimax Algorithm

The Minimax algorithm evaluates all possible moves to determine the best one for the AI. It uses a recursive approach with the following logic:

• Maximizes the AI's score.
• Minimizes the opponent's score.
• Stops recursion when a win, loss, or draw is detected, or a maximum depth is reached.

Future Enhancements

• Add support for larger board sizes and custom win conditions.
• Implement additional AI strategies (e.g., Alpha-Beta Pruning, Random AI).
• Add a GUI for better user interaction.

Contributing

Contributions are welcome! If you'd like to add a new feature or improve the AI, feel free to fork the repository and create a pull request.