public override void GradeBoards( MoveRepresentationList list, BoardRepresentation initialBoard )
{
int race = 1;
bool opponentFound = false;
for ( int i = 0; i < initialBoard.SquareCount() && race == 1; i++ )
{
if ( !opponentFound && initialBoard.GetPiecesAt( i ) < 0 )
opponentFound = true;
if ( opponentFound && initialBoard.GetPiecesAt( i ) > 0 )
race = 0;
}
for ( int i = 0; i < list.Count(); i++ )
{
int[] pubevalBoard = new int[28];
MoveRepresentation currentBoard = list.GetMoveRepresentation( i );
for ( int j = 0; j < currentBoard.SquareCount(); j++ )
pubevalBoard[j] = currentBoard.GetPiecesAt( j );
pubevalBoard[26] = currentBoard.BearOffCountCurrent();
pubevalBoard[27] = currentBoard.BearOffCountOpponent();
double s = PubevalGrade( race, pubevalBoard );
list.GetMoveRepresentation( i ).AddScore( s );
}
}
public bool EndTurn()
{
FindWinner();
if (m_Winner != BgPlayer.None)
{
BoardRepresentation finalBoard = new BoardRepresentation(this);
if (m_History.Count() > 0 && !m_History.PeekLast().PatternMatches(finalBoard))
{
m_History.Add(finalBoard);
m_History.Winner = m_Winner;
m_History.WinType = VictoryType();
}
return(false);
}
if (!IsMovesUsed())
{
if (DoesValidMoveExist())
{
return(false);
}
}
m_History.Add(new BoardRepresentation(this));
m_UndoStack.Clear();
m_CurrentPlayer = CurrentOpponentPlayer;
SetCorrectlySwitchedBoard();
RollDices();
m_MaxMovesPossible = MaxMovesPossible(0);
return(true);
}
public override void GradeBoards( MoveRepresentationList list, BoardRepresentation initialBoard )
{
for ( int i = 0; i < list.Count(); i++ )
{
double s = m_FuzzyController.ObtainBoardStrength( list.GetMoveRepresentation( i ) );
list.GetMoveRepresentation( i ).AddScore( s );
}
}
public override void GradeBoards( MoveRepresentationList list, BoardRepresentation initialBoard )
{
for ( int i = 0; i < list.Count(); i++ )
{
double s = m_Random.NextDouble() - m_Random.NextDouble();
list.GetMoveRepresentation( i ).AddScore( s );
}
}
public override LinguisticInputValue CreateLinguisticInputValue( BoardRepresentation board )
{
LinguisticInputValue result = new LinguisticInputValue( GetName(), 0 );
for ( int i = 1; i < 26; i++ )
if ( board.GetPiecesAt( i ) > 0 )
result.CrispValue = i;
return result;
}
public override bool AcceptDouble( BoardRepresentation board )
{
float[] output = Grade( board );
float totalWinSum = output[0] + output[1] + output[2];
if ( totalWinSum < 0.25f )
return false;
return true;
}
public override void GradeBoards( MoveRepresentationList list, BoardRepresentation initialBoard )
{
for ( int i = 0; i < list.Count(); i++ )
{
float[] output = Grade( list.GetMoveRepresentation( i ) );
double s = output[0] + (2 * output[1]) + (3 * output[2]) - (2 * output[3]) - (3 * output[4]);
list.GetMoveRepresentation( i ).AddScore( s );
}
}
public override bool AcceptDouble( BoardRepresentation board )
{
bool race = Race( board );
Grade( board, race, m_Output );
float totalWinSum = m_Output[0] + m_Output[1] + m_Output[2];
if ( totalWinSum < 0.25f )
return false;
return true;
}
public override bool Double( BoardRepresentation flippedBoard )
{
float[] output = Grade( flippedBoard );
float totalWinSum = output[0] + output[1] + output[2];
float gammonWinSum = output[1] + output[2];
if ( totalWinSum >= 0.66f && gammonWinSum < 0.5f )
return true;
return false;
}
public void Callibrate( BoardRepresentation[] winnerBoards, BoardRepresentation[] loserBoards )
{
AvgLinguisticInputResult[] avgWinnerInput = GetAverageInput( winnerBoards );
for ( int i = 0; i < avgWinnerInput.Length; i++ )
{
MfInterface[] memberFunctions = m_Controller.GetMembershipFunctions( avgWinnerInput[i].VariableName );
for ( int j = 0; j < memberFunctions.Length; j++ )
memberFunctions[j].AdjustToTargetPoint( avgWinnerInput[i].CrispValue, 0.05 );
}
}
public bool PatternMatches( BoardRepresentation repr )
{
int[] tmp = repr.m_BoardPattern;
if ( tmp.Length != m_BoardPattern.Length )
return false;
for ( int i = 0; i < m_BoardPattern.Length; i++ )
if ( m_BoardPattern[i] != tmp[i] )
return false;
return true;
}
public bool AcceptDouble()
{
if ( IsAgentPlaying( m_BgGame.CurrentPlayer ) )
{
BoardRepresentation board = new BoardRepresentation( m_BgGame );
int evaluator = m_GUI.SelectedEvaluator();
if ( evaluator >= 0 )
return m_Plugins[evaluator].AcceptDouble( board );
}
return true;
}
public override bool Double( BoardRepresentation flippedBoard )
{
bool race = Race( flippedBoard );
Grade( flippedBoard, race, m_Output );
float totalWinSum = m_Output[0] + m_Output[1] + m_Output[2];
float gammonWinSum = m_Output[1] + m_Output[2];
if ( totalWinSum >= 0.66f && gammonWinSum < 0.5f )
return true;
return false;
}
public BoardRepresentation Remove(int idx)
{
if (m_List.Count > idx)
{
BoardRepresentation result = Peek(idx);
m_List.RemoveAt(idx);
return(result);
}
else
{
return(null);
}
}
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 LinguisticInputValue CreateLinguisticInputValue( BoardRepresentation board )
{
bool opponentFound = false;
LinguisticInputValue result = new LinguisticInputValue( GetName(), 0 );
for ( int i = 0; i < 26; i++ )
{
if ( board.GetPiecesAt( i ) < 0 )
{
opponentFound = true;
}
if ( board.GetPiecesAt( i ) > 0 && opponentFound )
{
result.CrispValue = 1;
break;
}
}
return result;
}
public bool PatternMatches(BoardRepresentation repr)
{
int[] tmp = repr.m_BoardPattern;
if (tmp.Length != m_BoardPattern.Length)
{
return(false);
}
for (int i = 0; i < m_BoardPattern.Length; i++)
{
if (m_BoardPattern[i] != tmp[i])
{
return(false);
}
}
return(true);
}
private AvgLinguisticInputResult[] GetAverageInput( BoardRepresentation[] boards )
{
AvgLinguisticInputResult[] result = new AvgLinguisticInputResult[m_Controller.PreProcessorCount()];
LinguisticInputValue[] inValues = m_Controller.ObtainCrispInput( boards[0] );
for ( int i = 0; i < inValues.Length; i++ )
result[i] = new AvgLinguisticInputResult( inValues[i].VariableName, ( double )inValues[i].CrispValue );
for ( int i = 1; i < boards.Length; i++ )
{
inValues = m_Controller.ObtainCrispInput( boards[i] );
for ( int j = 0; j < inValues.Length; j++ )
result[j].CrispValue += ( double )inValues[j].CrispValue;
}
for ( int i = 0; i < result.Length; i++ )
result[i].CrispValue = result[i].CrispValue / ( double )boards.Length;
return result;
}
private void Train( BoardRepresentation currentBoard, float[] target )
{
int race = Race( currentBoard );
float[] input = BoardToNetworkInput( currentBoard );
m_NeuralNetworks[race].Train( input, target, 0.00001f, 0.2f );
}
private int Race( BoardRepresentation currentBoard )
{
int race = 1;
bool opponentFound = false;
for ( int j = 0; j < currentBoard.SquareCount() && race == 1; j++ )
{
if ( !opponentFound && currentBoard.GetPiecesAt( j ) < 0 )
opponentFound = true;
if ( opponentFound && currentBoard.GetPiecesAt( j ) > 0 )
race = 0;
}
return race;
}
private float[] Grade( BoardRepresentation currentBoard )
{
int race = Race( currentBoard );
float[] input = BoardToNetworkInput( currentBoard );
float[] output = new float[5];
m_NeuralNetworks[race].Run( input, output );
return output;
}
private float[] BoardToNetworkInput( BoardRepresentation currentBoard )
{
int Idx = 0;
float[] board = new float[196];
for ( int i = 1; i < 25; i++ )
{
int pieces = currentBoard.GetPiecesAt( i );
if ( pieces == 0 )
{
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == 1 )
{
board[Idx++] = 1;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == 2 )
{
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == 3 )
{
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces > 3 )
{
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = ( pieces - 3 ) / 2.0f;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == -1 )
{
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 1;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == -2 )
{
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 0;
board[Idx++] = 0;
}
else if ( pieces == -3 )
{
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 0;
}
else if ( pieces < -3 )
{
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 0;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = 1;
board[Idx++] = ( -pieces - 3 ) / 2.0f;;
}
}
board[Idx++] = currentBoard.GetPiecesAt( 25 ) / 2.0f;
board[Idx++] = -currentBoard.GetPiecesAt( 0 ) / 2.0f;
board[Idx++] = currentBoard.BearOffCountCurrent() / 15.0f;
board[Idx++] = -currentBoard.BearOffCountOpponent() / 15.0f;
return board;
}
public override LinguisticInputValue CreateLinguisticInputValue( BoardRepresentation board )
{
LinguisticInputValue result = new LinguisticInputValue( GetName(), -board.GetPiecesAt( 0 ) );
return result;
}
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 );
}
private void SetContactInput( BoardRepresentation board, float[] input )
{
for ( int i = 0; i < input.Length; i++ )
input[i] = 0.0f;
for ( int i = 0; i < 26; i++ )
{
m_OwnBoardView[i] = board.GetPiecesAt( i );
m_OppBoardView[25-i] = -board.GetPiecesAt( i );
}
int idx = 0;
idx = SetBoard( m_OwnBoardView, input, idx );
idx = SetContactBeardOff( m_OwnBoardView, input, idx );
idx = SetBar( m_OwnBoardView, input, idx );
idx = SetHalfContactInput( m_OwnBoardView, input, idx );
idx = SetHalfContactInput( m_OppBoardView, input, idx );
}
public void CalculateHitProbability( int position, int hitFrom, BoardRepresentation board, bool[,] hittingDices )
{
int distance = position - hitFrom;
for ( int i = 1; i <= 6; i++ )
{
for ( int j = 1; j <= 6; j++ )
{
if ( distance == i || distance == j )
{
if ( board.GetPiecesAt( 0 ) == 0 )
{
hittingDices[i-1,j-1] = true;
}
else if ( board.GetPiecesAt( 0 ) < 0 && hitFrom == 0 )
{
hittingDices[i-1,j-1] = true;
}
else if ( board.GetPiecesAt( 0 ) == -1 && hitFrom != 0 )
{
if ( distance == i && board.GetPiecesAt( j ) < 2 )
{
hittingDices[i-1,j-1] = true;
}
else if ( distance == j && board.GetPiecesAt( i ) < 2 )
{
hittingDices[i-1,j-1] = true;
}
}
else if ( i == j && ( board.GetPiecesAt( 0 ) == -1 || board.GetPiecesAt( 0 ) == -2 || board.GetPiecesAt( 0 ) == -3 ) && board.GetPiecesAt( i ) < 2 )
{
hittingDices[i-1,j-1] = true;
}
}
else if ( distance == i + j )
{
if ( board.GetPiecesAt( 0 ) == 0 )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 || board.GetPiecesAt( hitFrom + j ) < 2 )
hittingDices[i-1,j-1] = true;
}
else if ( board.GetPiecesAt( 0 ) == -1 && hitFrom == 0 )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 || board.GetPiecesAt( hitFrom + j ) < 2 )
hittingDices[i-1,j-1] = true;
}
else if ( i == j && ( board.GetPiecesAt( 0 ) == -1 || board.GetPiecesAt( 0 ) == -2 ) && board.GetPiecesAt( i ) < 2 )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 )
hittingDices[i-1,j-1] = true;
}
else if ( i == j && board.GetPiecesAt( 0 ) == -3 && hitFrom == 0 && board.GetPiecesAt( i ) < 2 )
{
hittingDices[i-1,j-1] = true;
}
}
else if ( i == j && ( distance == 3 * i || distance == 4 * i ) )
{
if ( board.GetPiecesAt( 0 ) == 0 )
{
if ( distance == 3 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
if ( distance == 4 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 && board.GetPiecesAt( hitFrom + ( i * 3 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
}
else if ( ( board.GetPiecesAt( 0 ) == -1 && hitFrom == 0 ) )
{
if ( distance == 3 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
if ( distance == 4 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 && board.GetPiecesAt( hitFrom + ( i * 3 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
}
else if ( ( board.GetPiecesAt( 0 ) == -2 && hitFrom == 0 ) )
{
if ( distance == 3 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
}
else if ( board.GetPiecesAt( 0 ) == -1 && hitFrom != 0 && board.GetPiecesAt( i ) < 2 )
{
if ( distance == 3 * i )
{
if ( board.GetPiecesAt( hitFrom + i ) < 2 && board.GetPiecesAt( hitFrom + ( i * 2 ) ) < 2 )
hittingDices[i-1,j-1] = true;
}
}
}
}
}
}
public override LinguisticInputValue CreateLinguisticInputValue( BoardRepresentation board )
{
LinguisticInputValue result = new LinguisticInputValue( GetName(), 0 );
float r = 0.0f;
for ( int i = 1; i < 25; i++ )
{
if ( board.GetPiecesAt( i ) == 1 )
{
bool[,] possibleDices = new bool[6,6];
for ( int x = 0; x < 6; x++ )
for ( int y = 0; y < 6; y++ )
possibleDices[x,y] = false;
for ( int j = 0; j < i; j++ )
if ( board.GetPiecesAt( j ) < 0 )
CalculateHitProbability( i, j, board, possibleDices );
int waysToBeHit = 0;
for ( int x = 0; x < 6; x++ )
for ( int y = 0; y < 6; y++ )
if ( possibleDices[x,y] )
waysToBeHit++;
float p = ( ((float)waysToBeHit) / 36.0f ) * 100;
r += ((24.0f - ((float)i-1))/24.0f) * p;
}
}
if ( r > 50.0f )
r = 50.0f;
result.CrispValue = (int)Math.Round( r, 0 );
return result;
}
public void Add(BoardRepresentation rep)
{
m_List.Add(rep);
}
public override void GradeBoards( MoveRepresentationList list, BoardRepresentation initialBoard )
{
bool race = Race( initialBoard );
for ( int i = 0; i < list.Count(); i++ )
{
Grade( list.GetMoveRepresentation( i ), race, m_Output );
float regularLoseProberbilety = 1.0f - ( m_Output[0] + m_Output[1] + m_Output[2] + m_Output[3] + m_Output[4] );
double equity = m_Output[0] + (2 * m_Output[1]) + (3 * m_Output[2]) - regularLoseProberbilety - (2 * m_Output[3]) - (3 * m_Output[4]);
list.GetMoveRepresentation( i ).AddScore( equity );
}
}
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 );
}
private void Train( BoardRepresentation board, bool race, float[] target )
{
if ( race )
{
SetRaceInput( board, m_RaceInput );
m_RaceNetwork.Train( m_RaceInput, target, MAX_SQUARE_ERROR, LEARNING_RATE );
}
else
{
SetContactInput( board, m_ContactInput );
m_ContactNetwork.Train( m_ContactInput, target, MAX_SQUARE_ERROR, LEARNING_RATE );
}
}
public override LinguisticInputValue CreateLinguisticInputValue( BoardRepresentation board )
{
LinguisticInputValue result = new LinguisticInputValue( GetName(), board.BearOffCountCurrent() );
return result;
}
public bool EndTurn()
{
FindWinner();
if ( m_Winner != BgPlayer.None )
{
BoardRepresentation finalBoard = new BoardRepresentation( this );
if ( m_History.Count() > 0 && !m_History.PeekLast().PatternMatches( finalBoard ) )
{
m_History.Add( finalBoard );
m_History.Winner = m_Winner;
m_History.WinType = VictoryType();
}
return false;
}
if ( !IsMovesUsed() )
if ( DoesValidMoveExist() )
return false;
m_History.Add( new BoardRepresentation( this ) );
m_UndoStack.Clear();
m_CurrentPlayer = CurrentOpponentPlayer;
SetCorrectlySwitchedBoard();
RollDices();
m_MaxMovesPossible = MaxMovesPossible( 0 );
return true;
}
private void Grade( BoardRepresentation board, bool race, float[] grade )
{
if ( race )
{
SetRaceInput( board, m_RaceInput );
m_RaceNetwork.Run( m_RaceInput, grade );
}
else
{
SetContactInput( board, m_ContactInput );
m_ContactNetwork.Run( m_ContactInput, grade );
}
}