private void AddSingleRow(MonteCarloResult data, int rowIndex)
{
int rowLength = data.data.GetLength(1);
for (int i = 0; i < rowLength; i++)
{
chartData.Series[rowIndex].Points.AddXY(i, data.data[rowIndex, i]);
}
}
private MonteCarloResult MonteCarlo(Board position, int depth)
{
// We've been told to cancel our search
if (cancellationToken.Cancelled)
{
return(new MonteCarloResult());
}
// We've reached the depth of our search, so blitz out the rest of the game and see who wins
if (depth <= 0)
{
return(Blitz(position));
}
List <int> moves = GetFilteredMoves(position);
// If we have no moves, return the evaluation of the position
if (moves.Count == 0)
{
return(Blitz(position));
}
MonteCarloResult best = new MonteCarloResult
{
Result = new SearchResult
{
Score = int.MinValue
}
};
foreach (int move in moves)
{
// Copy the board and make a move
Board copy = new Board(position);
copy.MakeMove(move, false, true);
// Recursively make the opponent's moves
MonteCarloResult counterMoveResult = MonteCarlo(copy, depth - 1);
best.PlayerOneWins += counterMoveResult.PlayerOneWins;
best.PlayerTwoWins += counterMoveResult.PlayerTwoWins;
if (position.Player == Player.One && counterMoveResult.PlayerOneScore > best.Result.Score)
{
best.Result.Score = counterMoveResult.PlayerOneScore;
best.Result.BestMove = move;
}
if (position.Player == Player.Two && counterMoveResult.PlayerTwoScore > best.Result.Score)
{
best.Result.Score = counterMoveResult.PlayerTwoScore;
best.Result.BestMove = move;
}
}
return(best);
}
private void CreateSeriesWithPoints(MonteCarloResult data)
{
int rowsCount = data.data.GetLength(0);
for (int i = 0; i < rowsCount; i++)
{
CreateSeries(i);
AddSingleRow(data, i);
}
}
public void Calculate_AllLosses__CalculatesCorrectly()
{
MonteCarloResult result = MonteCarloCalculator.Calculate(Count, Length, 0, 0.1f, 0.1f);
result.data.GetLength(0).ShouldBe(Count);
result.data.GetLength(1).ShouldBe(Length);
result.Wins.ShouldBe(0);
result.Losses.ShouldBe(Count);
result.WinsPcnt.ShouldBe(0f);
result.LossesPcnt.ShouldBe(1f);
}
public void GetPlotMin()
{
var monteCarloResult = new MonteCarloResult();
var sim = new OP("op1");
monteCarloResult.Collect(sim, -1);
monteCarloResult.Collect(sim, 4);
monteCarloResult.Function = "MIN";
var plot = monteCarloResult.GetPlot(10);
Assert.Single(plot.Bins.Keys);
Assert.Equal(-1, plot.Bins[1].Value);
}
public void GetPlotMaxMoreBins()
{
var monteCarloResult = new MonteCarloResult();
var sim = new OP("op1");
var sim2 = new OP("op2");
monteCarloResult.Collect(sim, -1);
monteCarloResult.Collect(sim, 4);
monteCarloResult.Collect(sim2, 0);
monteCarloResult.Collect(sim2, 1);
monteCarloResult.Function = "MAX";
var plot = monteCarloResult.GetPlot(10);
Assert.Equal(10, plot.Bins.Keys.Count);
}
public void CollectMinMax()
{
var monteCarloResult = new MonteCarloResult();
var op1 = new OP("op1");
var op2 = new OP("op2");
monteCarloResult.Collect(op1, 1);
monteCarloResult.Collect(op1, 2);
Assert.Equal(1, monteCarloResult.Min[op1]);
Assert.Equal(2, monteCarloResult.Max[op1]);
monteCarloResult.Collect(op2, -1);
monteCarloResult.Collect(op2, 4);
Assert.Equal(-1, monteCarloResult.Min[op2]);
Assert.Equal(4, monteCarloResult.Max[op2]);
}
public void LoadData(MonteCarloResult data)
{
chartData.Series.Clear();
CreateSeriesWithPoints(data);
}
public HistogramPlotViewModel(MonteCarloResult data)
{
PlotModel = data.GetPlot(Bins);
OxyPlotModel = CreateOxyPlotModel(ShowLabels);
Data = data;
}
private MonteCarloResult MonteCarlo(Board position, int depth, int extraDepth)
{
// We've been told to cancel our search
if (cancellationToken.Cancelled)
{
return(new MonteCarloResult());
}
// We've reached the depth of our search, so blitz out the rest of the game and see who wins
if (depth + extraDepth <= 0)
{
return(Blitz(position));
}
List <MonteCarloMove> moves = GetFilteredMoves(position).Select(x => new MonteCarloMove(x)).ToList();
// If we have no moves, return the evaluation of the position
if (moves.Count == 0)
{
return(Blitz(position));
}
MonteCarloResult best = new MonteCarloResult
{
Result = new SearchResult
{
Score = int.MinValue
}
};
bool pruned = true;
int pruningIterations = depth > _initialDepth - _pruningLayers ? _pruningIterations : 1;
for (int prune = 0; prune < pruningIterations && moves.Count > 0 && pruned; prune++)
{
foreach (var move in moves)
{
// Copy the board and make a move
Board copy = new Board(position);
copy.MakeMove(move.Index, false, true);
// Recursively make the opponent's moves
MonteCarloResult counterMoveResult = MonteCarlo(copy, depth - 1, prune * _pruningDepthPerIteration);
best.PlayerOneWins += counterMoveResult.PlayerOneWins;
best.PlayerTwoWins += counterMoveResult.PlayerTwoWins;
move.Evaluation = position.Player == Player.One ? counterMoveResult.PlayerOneScore : counterMoveResult.PlayerTwoScore;
if (position.Player == Player.One && counterMoveResult.PlayerOneScore > best.Result.Score)
{
best.Result.Score = counterMoveResult.PlayerOneScore;
best.Result.BestMove = move.Index;
}
if (position.Player == Player.Two && counterMoveResult.PlayerTwoScore > best.Result.Score)
{
best.Result.Score = counterMoveResult.PlayerTwoScore;
best.Result.BestMove = move.Index;
}
}
// Remove the worst moves
pruned = false;
int newCount = moves.Count / _pruningDivisor;
if (newCount >= 2)
{
moves.Sort((c, n) => n.Evaluation.CompareTo(c.Evaluation));
for (int i = moves.Count - 1; i > newCount; i--)
{
moves.RemoveAt(i);
pruned = true;
}
}
}
return(best);
}
