Checkers

Phase 1. Core Board & Piece Engine

Implement the foundational checkers board, pieces, and movement logic.

• Represent an 8×8 board with dark/light squares.
• Implement basic diagonal movement.
• Restrict moves to valid squares.
• Provide ASCII rendering for debugging.

Functional result: A functional internal board where pieces can move diagonally on valid squares. The system correctly updates piece positions and allows simple non-capturing moves for both players.

Phase 2. Game State Manager (Turns, Captures, Forced Captures)

Build the core game rules for capturing and turn control.

• Enforce alternating turns.
• Implement simple captures.
• Enforce mandatory captures.
• Track move history.

Functional result: A turn-based engine enabling legal moves, captures, and mandatory-jump enforcement. The game state updates consistently, only allowing a player to finish a turn after completing required captures.

Phase 3. Promotion, Multiple Jumps & King Rules

Implement advanced checkers mechanics for full rule compliance.

• Promote pieces to kings.
• Allow kings bidirectional movement.
• Implement multi-jump chains.
• Validate all advanced move sequences.

Functional result: A complete rules engine handling full promotions and multi-jump sequences. Kings move in both directions, and the system ensures all chained captures follow official rules.

Phase 4. Graphical Interface (Tkinter or Pygame)

Build an interactive visual board to play checkers.

• Render the board and pieces graphically.
• Allow mouse-based moves.
• Highlight legal moves and jumps.
• Display captures and turn indicator.

Functional result: A GUI where players select pieces, see valid moves, and make turns visually. The board updates in real time and reflects all rules, including mandatory captures and promotions.

Phase 5. AI Opponent (Minimax + Heuristics)

Implement an intelligent computer opponent with strategic play.

• Use minimax with alpha-beta pruning.
• Design evaluation heuristics (mobility, kings, captures).
• Add difficulty levels by search depth.

Functional result: A human-vs-AI mode where the computer produces legal, strategic moves. The AI responds based on configurable difficulty levels, using heuristics and pruning for efficient decision-making.

Phase 6. Persistence, Notation Support & Replay Tools

Add saving, loading, and analysis functionalities.

• Save/load games in a custom notation format.
• Implement move replay and navigation.
• Provide basic textual position evaluation.

Functional result: A system that stores full matches, reloads them, and replays moves one by one. Players can inspect past positions and continue previous games with full state consistency.