protected void Page_Load(object sender, EventArgs e)
{
Session.Timeout = 5;
this.board = this.Session["board"] as CheckersBoard;
this.alg = this.Session["alg"] as Algorithms;
this.gameHistory = this.Session["gameHistory"] as List<CheckersMove>;
if (this.Session["AIID"] != null)
this.AIID = this.Session["AIID"].ToString()[0];
if (board != null && alg != null && this.gameHistory != null && !this.board.GameIsOver())
{
this.board.MakeMove(parsePlayerMove());
if (!board.GameIsOver())
{
this.computerMove();
this.generateBoardElements();
}
if (this.board.GameIsOver())
{
this.winner.Text = this.board.Winner == 1 ? "The player RED is the winner." : "The player BLACK is the winner.";
Response.Redirect("~/Results.aspx");
}
}
}
private static object threadProc(Object data)
{
Individual[] weights = data as Individual[];
Algorithms alg = new Algorithms(new CheckersPlayer(1));
CheckersBoard whiteBoard = new CheckersBoard(0, weights[0].Weights);
CheckersBoard blackBoard = new CheckersBoard(0, weights[1].Weights);
whiteBoard.GameMaxLength = 150;
blackBoard.GameMaxLength = 150;
while (!blackBoard.GameIsOver())
{
CheckersMove move = alg.ABNegamax(blackBoard, weights[1].SearchDepth, 0, double.MinValue, double.MaxValue) as CheckersMove;
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
if (blackBoard.GameIsOver())
break;
else
{
move = alg.ABNegamax(whiteBoard, weights[0].SearchDepth, 0, double.MinValue, double.MaxValue) as CheckersMove;
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
}
}
switch (whiteBoard.Winner)
{
case 0:
weights[0].Draws += 1;
weights[1].Draws += 1;
break;
case 1:
weights[0].TotalWhiteWins += 1;
weights[1].Loses += 1;
break;
case -1:
weights[1].TotalBlackWins += 1;
weights[0].Loses += 1;
break;
}
return weights as object;
}
static object ThreadProcAdaptive(Object data)
{
Individual[] weights = data as Individual[];
GameAI.Algorithms alg = new Algorithms(new CheckersPlayer(1));
CheckersBoard whiteBoard = new CheckersBoard(0, weights[0].Weights);
CheckersBoard blackScore = new CheckersBoard(0, weights[0].Weights);
CheckersBoard blackBoard = new CheckersBoard(0, weights[1].Weights);
whiteBoard.GameMaxLength = 200;
blackBoard.GameMaxLength = 200;
while (!blackBoard.GameIsOver())
{
CheckersMove move = alg.ABNegamax(blackBoard, weights[1].SearchDepth, 0, double.MinValue, double.MaxValue) as CheckersMove;
List<IMove> opponentsMoves = alg.EvaluateMoves(blackScore, weights[0].SearchDepth, 0, double.MinValue, double.MaxValue);
whiteBoard.MakeMove(move);
blackScore.MakeMove(move);
blackBoard.MakeMove(move);
if (blackBoard.GameIsOver())
break;
else
{
move = alg.AdaptiveABNegamax(whiteBoard, weights[0].SearchDepth, 0, double.MinValue, double.MaxValue, opponentsMoves, move) as CheckersMove;
whiteBoard.MakeMove(move);
blackScore.MakeMove(move);
blackBoard.MakeMove(move);
}
}
switch (whiteBoard.Winner)
{
case 0:
weights[0].Draws += 1;
weights[1].Draws += 1;
break;
case 1:
weights[0].TotalWhiteWins += 1;
weights[1].Loses += 1;
break;
case -1:
weights[1].TotalBlackWins += 1;
weights[0].Loses += 1;
break;
}
return weights as object;
}
/// <summary>
/// This procedure takes two individuals and makes them play against each other
/// </summary>
/// <param name="data">Should be an array of doubles representing two individuals</param>
/// <returns>The individuals after playing against each other</returns>
static object ThreadProc(Object data)
{
Individaul[] weights = data as Individaul[];
GameAI.Algorithms alg = new Algorithms(new CheckersPlayer(1));
CheckersBoard whiteBoard = new CheckersBoard(0, weights[0].Weights);
CheckersBoard blackBoard = new CheckersBoard(0, weights[1].Weights);
whiteBoard.GameMaxLength = 200;
blackBoard.GameMaxLength = 200;
while (!blackBoard.GameIsOver())
{
CheckersMove move = alg.ABNegamax(blackBoard, 4, 0, double.MinValue, double.MaxValue) as CheckersMove;
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
if (blackBoard.GameIsOver())
break;
else
{
move = alg.ABNegamax(whiteBoard, 4, 0, double.MinValue, double.MaxValue) as CheckersMove;
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
}
}
switch (whiteBoard.Winner)
{
case 0:
weights[0].AddToFitness(1);
weights[1].AddToFitness(1);
break;
case 1:
weights[0].AddToFitness(3);
break;
case -1:
weights[1].AddToFitness(3);
break;
}
return weights as object;
}
//, GameAI.Algorithms alg)
static object ThreadProc(Object data, string path)
{
Individual[] weights = data as Individual[];
GameAI.Algorithms alg = new Algorithms(new CheckersPlayer(1));
CheckersBoard whiteBoard = new CheckersBoard(0, weights[0].Weights);
CheckersBoard blackBoard = new CheckersBoard(0, weights[1].Weights);
whiteBoard.GameMaxLength = 200;
blackBoard.GameMaxLength = 200;
while (!blackBoard.GameIsOver())
{
CheckersMove move = alg.ABNegamax(blackBoard, weights[1].SearchDepth, 0, double.MinValue, double.MaxValue) as CheckersMove;
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
if (blackBoard.GameIsOver())
break;
else
{
//move = alg.ABNegamax(whiteBoard, weights[0].SearchDepth, 0, double.MinValue, double.MaxValue) as CheckersMove;
move = alg.POSM(whiteBoard, 0.5) as CheckersMove;
// writer.WriteLine(move.GetMoveScore().ToString());
whiteBoard.MakeMove(move);
blackBoard.MakeMove(move);
}
}
FileStream file = new FileStream(path, FileMode.Append, FileAccess.Write);
StreamWriter wr = new StreamWriter(file);
switch (whiteBoard.Winner)
{
case 0:
weights[0].Draws += 1;
weights[1].Draws += 1;
wr.WriteLine("Draw");
wr.WriteLine(alg.ToString());
break;
case 1:
weights[0].TotalWhiteWins += 1;
weights[1].Loses += 1;
wr.WriteLine("Win for Adaptive");
alg.GameObervationUpdate(1);
wr.WriteLine(alg.ToString());
break;
case -1:
weights[1].TotalBlackWins += 1;
weights[0].Loses += 1;
wr.WriteLine("Los for Adaptive");
alg.GameObervationUpdate(-1);
wr.WriteLine(alg.ToString());
break;
}
wr.Close();
file.Close();
return weights as object;
}