Algerian/Spanish Checkers download

Algerian / Spanish Checkers Variant is a digital implementation of the classic board game with unique features and rules.
Currently, the program integrates an AI opponent using the Minimax algorithm with alpha-beta pruning. The previous versions just favours moves that result in the fewest captures for the opponent.
Future versions will include more sophisticated AI to enhance gameplay. The program currently handles all kind of regular piece and dama moves and captures.

Features

Mandatory Capturing: Players must capture opponent pieces if possible, making strategic planning essential.
Multi-Capture Moves: Players can capture multiple pieces in one turn if the conditions allow, which adds depth to the strategy.
Promotion to Damas: When a piece reaches the opponent's back row, it is promoted to a Dama (king), which has enhanced movement capabilities.
User Interface and Interaction
Graphical Board Display: The game board is visually represented with pieces displayed on an 8x8 grid.
Piece Selection and Movement: The players interacts with the game by selecting pieces and choosing valid moves on the board.
Additional Features
Best Move Calculation: The AI selects the best move by evaluating all possible moves using the Minimax algorithm and alpha-beta pruning. If multiple moves have the same evaluation score, a secondary method, such as randomization based on current time or other factors, is used to diversify the AI's choices.
Search Depth: Due to time constraints, the search depth for the Minimax algorithm is limited to 10 half-moves. This depth limitation ensures that the AI can provide a response within a reasonable timeframe, though future versions may increase this depth for deeper analysis.
Turn-Based System: The game alternates turns between two players, managing the flow of gameplay.
Undo/Redo Functionality: Players can undo or redo their moves, providing flexibility and error correction during play.
Planned Future Features
Depth Limitation: The search depth is constrained to 10 half-moves to ensure the AI operates within a reasonable timeframe. Future versions will aim to increase the search depth to enhance decision-making quality.
Advanced Move Analysis: Future updates might introduce features like move hints, analysis of potential outcomes, and other AI-driven enhancements.
Evaluation Function: The present evaluation function only accounts for piece count. Future enhancements will expand this function to consider additional factors such as piece positioning, mobility, and capture potential, improving the overall strategic decision-making of the AI.
Integration of Other AI Approaches: Additional AI methodologies will be explored and integrated to further enhance the AI's strategic capabilities and decision-making processes.