Othello

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Othello/Reversi game coded in C++. Can play against an 'AI'.

• Since you're here, I assume you already know how to play... If not, here's a link.
• To play the game,
  1. Run the main binary file and follow the prompts, or
  2. Download the source code and run make to compile, then run the main binary file.

Disclaimer: If you are on Windows then you may need to compile the code yourself; the provided Makefile and binary executable was meant for Unix-based systems.

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Game modes

1. Player vs Player
2. Player vs AI
3. AI vs AI
4. Puzzle Mode

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Features

• Beautiful TUI — Unicode board with box-drawing borders, a filled ● for White and hollow ○ for Black, and valid moves highlighted in green.
• AI time limit can be set to any positive integer (seconds), default = 5. In AI vs AI mode each side has its own time limit.
• In PvE mode the player can choose their disk color and consequently, who starts first.
• Undo (U) — reverts your last move. In PvE mode, undoes back to the player's own last turn, skipping over the AI's move.
• Resign (R) — immediately concedes the game and awards the win to the opponent.
• Game log export — at the end of every game, two files are saved to the logs/ folder:
  • .log — raw move sequence on a single line
  • .txt — human-readable log with move history, scores, result, and game settings

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Puzzle Mode

Puzzle Mode lets you load a custom board position and watch the AI play both sides from that state.

Setup:

1. Choose a board input format:
   • FEN-like string — rows separated by /, using B/b (Black), W/w (White), and digits 1–8 for empty cells. Example: 8/8/8/3WB3/3BW3/8/8/8
   • 64-character string — left-to-right, top-to-bottom using B/b, W/w, and . for empty. Example: ...........................WB......BW...........................
2. Specify whose turn it is (B for Black, W for White).
3. Set a time limit for the AI (shared by both sides).

The AI then plays out the game from the given position.

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Notes on 'AI'

• Search: Iterative deepening (IDDFS) with a time limit.
• Algorithm: NegaScout (Principal Variation Search).
• Move ordering: Moves are tried in priority order (corners → edges → inner cells → X-squares) to improve pruning efficiency.
• Evaluation components:
  • Material: positional weights per square
  • Mobility: relative number of legal moves available
  • Stability: discs that can never be flipped (corners, filled edges, enclosed interior)
  • Frontier: discs adjacent to empty squares (fewer is better)
• Dynamic danger correction: static penalties for X/C-squares are lifted when the adjacent corner is already owned, since those squares are no longer a liability.