- Made the getBoardState method in Referee.java static.
- Created NeuralNetworkPlayer.java, though I don't know how to make the computer use it.
- Updated the Player interface to include passing the PlayerModel. Most of the current com agents ignore the data, but it is now available.
- Updated the train function in PlayerModel.java.
- Integrated the ANN with the game. The network now predicts a user move, completely ignores it, and trains itself on the players actual move. This integration also included implementing two new functions. The first translates a board state to a boolean array to correspond with input nodes. The second translates a move to a boolean array to correspond with output nodes.
- Added support for the player model inside Referee.java; high scores should now persist over a single execution of the program.
- Refactored PlayerModel.java to support game logging. All games are now logged so that we can track overall progress.
- Added scaffolding to allow saving and importing of PlayerModel.java. It is not yet functional, but it will be with two function implementations and then the appropriate calls.
- Updated the PlayerModel to fix a bug in the high score tracking.
- Created HighScoreDialog.java, which displays the high scores from a PlayerModel. In the future, it will have a "New Game" button so that it can be used to transition between games.
