Connect 6 Game

A modern implementation of the Connect 6 game with an advanced AI opponent using the Minimax algorithm with Alpha-Beta pruning.

Table of Contents

• Connect 6 Game
  • Table of Contents
  • Features
  • Screenshots
    • Main Menu
    • Game Menu
    • Gameplay
  • Installation
    • Prerequisites
    • Building from Source
    • Building on Different Platforms
      • Windows
      • macOS
      • Linux
  • Game Rules
    • Key Rules
  • AI Implementation
  • Project Structure
  • Development
    • Setting Up Development Environment
    • Running Tests
  • Contributing
    • Development Workflow
    • Code Style
  • License
  • Acknowledgments

Features

• 🎮 Multiple game modes:
  • Player vs Player
  • Player vs AI
  • AI vs AI
• 🤖 AI with three difficulty levels:
  • Easy (1-ply search)
  • Medium (3-ply search)
  • Hard (5-ply search)
• 🎯 Advanced AI using Minimax with Alpha-Beta pruning
• 💾 Save/Load game functionality
• 🎨 Modern UI with animations
• 📱 Cross-platform support
• 🔍 Detailed game statistics and analysis
• 🎯 Customizable board size (default 15x15)
• 💾 Game replay functionality

Screenshots

Main Menu

Game Menu

Gameplay

Installation

Prerequisites

• Qt 6.0 or higher
• C++17 compatible compiler
• CMake 3.15 or higher

Building from Source

# Clone the repository
git clone git@github.com:impelixx/connect_6.git
cd connect6

# Create and enter build directory
mkdir build && cd build

# Configure and build
cmake ..
make


./connect6

Building on Different Platforms

Windows

cmake -G "Visual Studio 17 2022" ..
cmake --build . --config Release

macOS

cmake -G "Xcode" ..
cmake --build . --config Release

Linux

cmake -G "Unix Makefiles" ..
make

Game Rules

Connect 6 is a two-player game played on a 15x15 board. Players take turns placing their pieces (black and white) on the board. The first player to create a line of 6 or more pieces in any direction (horizontal, vertical, or diagonal) wins the game.

Key Rules

1. Players alternate turns placing one piece per turn
2. Black moves first
3. A win is achieved by creating a line of 6 or more pieces
4. Lines can be horizontal, vertical, or diagonal
5. The game ends in a draw if the board is filled without a winner

AI Implementation

The game features an advanced AI opponent that uses:

• Minimax algorithm with Alpha-Beta pruning
• Pattern recognition for move evaluation
• Center control strategy
• Move ordering optimization

For detailed information about the AI implementation, see Algorithm Documentation.

Project Structure

connect6/
├── src/                    # Source code
│   ├── ai/                # AI implementation
│   ├── gui/               # User interface
│   ├── core/              # Game logic
│   └── utils/             # Utility functions
├── include/               # Header files
├── tests/                 # Unit tests
├── docs/                  # Documentation
├── resources/             # Game resources
└── build/                 # Build directory

Development

Setting Up Development Environment

1. Install required dependencies:

   # Ubuntu/Debian
   sudo apt-get install qt6-base-dev cmake build-essential
   
   # macOS
   brew install qt@6 cmake
   
   # Windows
   # Install Qt 6 and Visual Studio

2. Configure development tools:

   # Enable debug build
   cmake -DCMAKE_BUILD_TYPE=Debug ..

Running Tests

cd build
ctest --output-on-failure

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Development Workflow

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Code Style

• Follow the Google C++ Style Guide
• Use meaningful variable and function names
• Add comments for complex logic
• Write unit tests for new features

License

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

Acknowledgments

• Qt Framework for the GUI
• Modern C++ features for performance optimization
• Alpha-Beta pruning algorithm for AI optimization
• Contributors and maintainers of the project