How bangtri/gamecaro works
GameCaRo is a desktop Caro (five-in-a-row) game. A player selects a cell in the Swing interface; the interface updates the board, checks for a win, and—when it is the AI’s turn—asks the search engine for a move and displays it. The AI evaluates candidate positions and searches board states with alpha-beta pruning. The excerpts show these core interactions; other documented capabilities are not described in the README, so none are inferred.
Main entry points: AlphaBetaPrunning.java Move search · MainView.java Swing game view · CaroBoard.java Caro board · State.java Move state
Components 5
Game interface
- Swing game view
src/gamecaro/MainView.java
Game state
- Caro board
src/gamecaro/CaroBoard.java
AI engine
- Move search
src/gamecaro/AlphaBetaPrunning.java - Move state
src/gamecaro/State.java
Other components
- Human player
Connections 6
- Human player → Swing game view: selects move
- Swing game view → Caro board: updates board
- Swing game view → Move search: requests move
- Move search → Caro board: evaluates positions
- Move search → Move state: creates candidates
- Move search → Swing game view: returns move