public GammonInterface( bool nackgammon, bool maxFivePiecesOnPoint )
{
m_Board = new BgBoard( nackgammon );
m_BgDiceCup = new BgDiceCup();
m_Moves = new int[4];
m_Cube = new Cube();
m_UndoStack = new UndoStack();
m_History = new GameHistory();
NewGame( nackgammon, maxFivePiecesOnPoint );
}
public GammonInterface(bool nackgammon, bool maxFivePiecesOnPoint)
{
m_Board = new BgBoard(nackgammon);
m_BgDiceCup = new BgDiceCup();
m_Moves = new int[4];
m_Cube = new Cube();
m_UndoStack = new UndoStack();
m_History = new GameHistory();
NewGame(nackgammon, maxFivePiecesOnPoint);
}
public override void Learn( GameHistory history )
{
m_Trained = true;
BoardRepresentation[] looserBoards = new BoardRepresentation[history.Count() / 2];
int looserIdx = looserBoards.Length;
for ( int i = history.Count()-2; i >= 0; i -= 2 )
looserBoards[--looserIdx] = history.Peek( i );
BoardRepresentation[] winnerBoards = new BoardRepresentation[history.Count() - looserBoards.Length];
int winnerIdx = winnerBoards.Length;
for ( int i = history.Count()-1; i >= 0; i -= 2 )
winnerBoards[--winnerIdx] = history.Peek( i );
m_FuncCallibrator.Callibrate( winnerBoards, looserBoards );
}
public override void Learn( GameHistory history )
{
BoardRepresentation[] looserBoards = new BoardRepresentation[history.Count() / 2];
int looserIdx = looserBoards.Length;
for ( int i = history.Count()-2; i >= 0; i -= 2 )
looserBoards[--looserIdx] = history.Peek( i );
BoardRepresentation[] winnerBoards = new BoardRepresentation[history.Count() - looserBoards.Length];
int winnerIdx = winnerBoards.Length;
for ( int i = history.Count()-1; i >= 0; i -= 2 )
winnerBoards[--winnerIdx] = history.Peek( i );
int wIdx = winnerBoards.Length - 1;
int lIdx = looserBoards.Length - 1;
float[] wTarget = Grade( winnerBoards[wIdx] );;
float[] lTarget = Grade( looserBoards[lIdx] );
if ( history.WinType == 1 )
{
wTarget[0] = wTarget[0] + ( 0.1f * ( 1.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( 0.1f * ( 0.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( 0.1f * ( 0.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( 0.1f * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( 0.1f * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( 0.1f * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( 0.1f * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( 0.1f * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( 0.1f * ( 0.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( 0.1f * ( 0.0f - lTarget[4] ) );
}
else if ( history.WinType == 2 )
{
wTarget[0] = wTarget[0] + ( 0.1f * ( 0.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( 0.1f * ( 1.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( 0.1f * ( 0.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( 0.1f * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( 0.1f * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( 0.1f * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( 0.1f * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( 0.1f * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( 0.1f * ( 1.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( 0.1f * ( 0.0f - lTarget[4] ) );
}
else if ( history.WinType == 3 )
{
wTarget[0] = wTarget[0] + ( 0.1f * ( 0.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( 0.1f * ( 0.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( 0.1f * ( 1.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( 0.1f * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( 0.1f * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( 0.1f * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( 0.1f * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( 0.1f * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( 0.1f * ( 0.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( 0.1f * ( 1.0f - lTarget[4] ) );
}
while ( lIdx >= 0 || wIdx >= 0 )
{
if ( wIdx >= 0 )
{
Train( winnerBoards[wIdx], wTarget );
if ( wIdx > 0 )
{
float[] prevWState = Grade( winnerBoards[wIdx-1] );
wTarget[0] = prevWState[0] + ( 0.1f * ( wTarget[0] - prevWState[0] ) );
wTarget[1] = prevWState[1] + ( 0.1f * ( wTarget[1] - prevWState[1] ) );
wTarget[2] = prevWState[2] + ( 0.1f * ( wTarget[2] - prevWState[2] ) );
wTarget[3] = prevWState[3] + ( 0.1f * ( wTarget[3] - prevWState[3] ) );
wTarget[4] = prevWState[4] + ( 0.1f * ( wTarget[4] - prevWState[4] ) );
}
wIdx--;
}
if ( lIdx >= 0 )
{
Train( looserBoards[lIdx], lTarget );
if ( lIdx > 0 )
{
float[] prevLState = Grade( looserBoards[lIdx-1] );
lTarget[0] = prevLState[0] + ( 0.1f * ( lTarget[0] - prevLState[0] ) );
lTarget[1] = prevLState[1] + ( 0.1f * ( lTarget[1] - prevLState[1] ) );
lTarget[2] = prevLState[2] + ( 0.1f * ( lTarget[2] - prevLState[2] ) );
lTarget[3] = prevLState[3] + ( 0.1f * ( lTarget[3] - prevLState[3] ) );
lTarget[4] = prevLState[4] + ( 0.1f * ( lTarget[4] - prevLState[4] ) );
}
lIdx--;
}
}
m_GamesTrained++;
if ( m_GamesTrained % 100 == 0 )
Save( SAVE_FILE );
}
public override void Learn( GameHistory history )
{
BoardRepresentation[] boards = new BoardRepresentation[history.Count()];
for ( int i = boards.Length-1; i >= 0; i-- )
boards[i] = history.Peek( i );
int idx = boards.Length-1;
int firstRaceBoardIdx = idx;
for ( int i = 0; i < boards.Length; i++ )
{
if ( Race( boards[i] ) )
{
firstRaceBoardIdx = i;
break;
}
}
float[] wTarget = new float[5];
float[] lTarget = new float[5];
Grade( boards[idx], idx > firstRaceBoardIdx, wTarget );
Grade( boards[idx-1], (idx-1) > firstRaceBoardIdx, lTarget );
if ( history.WinType == 1 )
{
wTarget[0] = wTarget[0] + ( STEP_SIZE * ( 1.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( STEP_SIZE * ( 0.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( STEP_SIZE * ( 0.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( STEP_SIZE * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( STEP_SIZE * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( STEP_SIZE * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( STEP_SIZE * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( STEP_SIZE * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( STEP_SIZE * ( 0.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( STEP_SIZE * ( 0.0f - lTarget[4] ) );
}
else if ( history.WinType == 2 )
{
wTarget[0] = wTarget[0] + ( STEP_SIZE * ( 0.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( STEP_SIZE * ( 1.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( STEP_SIZE * ( 0.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( STEP_SIZE * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( STEP_SIZE * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( STEP_SIZE * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( STEP_SIZE * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( STEP_SIZE * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( STEP_SIZE * ( 1.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( STEP_SIZE * ( 0.0f - lTarget[4] ) );
}
else if ( history.WinType == 3 )
{
wTarget[0] = wTarget[0] + ( STEP_SIZE * ( 0.0f - wTarget[0] ) );
wTarget[1] = wTarget[1] + ( STEP_SIZE * ( 0.0f - wTarget[1] ) );
wTarget[2] = wTarget[2] + ( STEP_SIZE * ( 1.0f - wTarget[2] ) );
wTarget[3] = wTarget[3] + ( STEP_SIZE * ( 0.0f - wTarget[3] ) );
wTarget[4] = wTarget[4] + ( STEP_SIZE * ( 0.0f - wTarget[4] ) );
lTarget[0] = lTarget[0] + ( STEP_SIZE * ( 0.0f - lTarget[0] ) );
lTarget[1] = lTarget[1] + ( STEP_SIZE * ( 0.0f - lTarget[1] ) );
lTarget[2] = lTarget[2] + ( STEP_SIZE * ( 0.0f - lTarget[2] ) );
lTarget[3] = lTarget[3] + ( STEP_SIZE * ( 0.0f - lTarget[3] ) );
lTarget[4] = lTarget[4] + ( STEP_SIZE * ( 1.0f - lTarget[4] ) );
}
bool isCurrentBoardWinner = true;
float[] prevWState = new float[5];
float[] prevLState = new float[5];
while ( idx >= 0 )
{
if ( isCurrentBoardWinner )
{
Train( boards[idx], idx > firstRaceBoardIdx, wTarget );
idx--;
if ( idx > 0 )
{
Grade( boards[idx-1], idx-1 > firstRaceBoardIdx, prevWState );
wTarget[0] = prevWState[0] + ( STEP_SIZE * ( wTarget[0] - prevWState[0] ) );
wTarget[1] = prevWState[1] + ( STEP_SIZE * ( wTarget[1] - prevWState[1] ) );
wTarget[2] = prevWState[2] + ( STEP_SIZE * ( wTarget[2] - prevWState[2] ) );
wTarget[3] = prevWState[3] + ( STEP_SIZE * ( wTarget[3] - prevWState[3] ) );
wTarget[4] = prevWState[4] + ( STEP_SIZE * ( wTarget[4] - prevWState[4] ) );
}
}
else
{
Train( boards[idx], idx > firstRaceBoardIdx, lTarget );
idx--;
if ( idx > 0 )
{
Grade( boards[idx-1], idx-1 > firstRaceBoardIdx, prevLState );
lTarget[0] = prevLState[0] + ( STEP_SIZE * ( lTarget[0] - prevLState[0] ) );
lTarget[1] = prevLState[1] + ( STEP_SIZE * ( lTarget[1] - prevLState[1] ) );
lTarget[2] = prevLState[2] + ( STEP_SIZE * ( lTarget[2] - prevLState[2] ) );
lTarget[3] = prevLState[3] + ( STEP_SIZE * ( lTarget[3] - prevLState[3] ) );
lTarget[4] = prevLState[4] + ( STEP_SIZE * ( lTarget[4] - prevLState[4] ) );
}
}
isCurrentBoardWinner = !isCurrentBoardWinner;
}
m_GamesTrained++;
if ( m_GamesTrained % 100 == 0 )
Save( SAVE_FILE );
}
public override void Learn( GameHistory history )
{
}