Chinese Chess Game with Minimax AI

This project implements a classic Chinese Chess (Xiangqi) game using Python and Pygame, allowing players to challenge a computer opponent powered by the Minimax algorithm.

Features

• Visual Game Interface: Play the game with a visually appealing and intuitive interface using Pygame.
• Human vs. AI: Challenge the computer opponent using the Minimax algorithm, which evaluates possible moves to make optimal decisions.
• Game Rules: Adheres to the standard rules of Chinese Chess, including piece movements, special moves (e.g., Cannon, Horse), and checkmate conditions.
• Turn-Based Gameplay: Play takes place in alternating turns, with each player moving one piece at a time.

Getting Started

Installation

1. Install Python: If you don't have Python, download and install it from https://www.python.org/.
2. Install Pygame:

   pip install pygame

Running the Game

1. Clone the Repository:

   git clone https://github.com/your-username/chinese-chess-minimax  # Replace with your repository URL

2. Navigate to the Project Directory:

   cd <repo name> 

3. Run the Game:

   python main.py

Game Mechanics

• Pieces: The game uses traditional Chinese Chess pieces:
  • General (帥/将): Can only move one square horizontally or vertically within its palace.
  • Advisor (仕/士): Can only move diagonally within its palace.
  • Elephant (相/象): Can move two squares diagonally, but cannot cross the river (the middle line of the board).
  • Rook (車/俥): Can move horizontally or vertically any number of squares.
  • Cannon (炮/砲): Can move horizontally or vertically any number of squares, but to capture a piece, it must jump over another piece.
  • Horse (馬/马): Can move two squares horizontally or vertically, then one square perpendicularly.
  • Soldier (兵/卒): Can move one square forward, but cannot move backward.
• Checkmate: The game ends when the General is checkmated (under attack with no escape) by the opponent's pieces.
• Stalemate: The game ends in a draw if the player whose turn it is to move has no legal move to make, even though their General is not under attack.

AI Implementation (Minimax Algorithm)

• Minimax: The algorithm recursively explores possible moves, evaluating the game state after each move.
• Heuristic Evaluation: A scoring function is used to evaluate the strength of each game state (higher scores indicate a favorable position for the AI).
• Depth Limit: The algorithm searches a limited number of moves ahead to balance performance and accuracy.

Future Enhancements

• Improved Heuristic Function: Implement a more sophisticated scoring function to enhance the AI's strength.
• Opening Book: Add a database of common opening moves for more strategic gameplay.
• Multiplayer Mode: Allow two human players to compete against each other.
• GUI Enhancements: Improve the visual aesthetics and user experience.

Contributing

Contributions are welcome! You can contribute by:

• Bug Fixes: Report and fix bugs.
• Feature Enhancements: Implement new features or improve existing ones.
• Documentation: Improve the README and other documentation.

Please follow the standard Git workflow for contributing.

Let me know if you need further assistance.