public double Evaluate(IPlayerNode node)
{
if (node.GameOver)
{
return(-10000000);
}
var result = Heuristics.GetMonotonicity(node.Grid) * 10 + Heuristics.GetEmptyCellCount(node.Grid);
return(result);
}
public double Evaluate(IPlayerNode node)
{
if (node.GameOver)
{
return -10000000;
}
var result = Heuristics.GetMonotonicity(node.Grid) * 10 + Heuristics.GetEmptyCellCount(node.Grid);
return result;
}
private void Visit(IPlayerNode node, int searchDepth)
{
if (searchDepth == 0)
{
return;
}
foreach (var child in node.Children.Values)
{
this.Visit(child, searchDepth);
}
}
private void Visit(IPlayerNode node, int searchDepth)
{
if (searchDepth == 0)
{
return;
}
foreach (var child in node.Children.Values)
{
this.Visit(child, searchDepth);
}
}
private double GetPositionEvaluation(IPlayerNode playerNode, int depth, double probability)
{
this.searchStatistics.NodeCount++;
if (playerNode.GameOver || probability < this.minProbability || depth == 0)
{
this.searchStatistics.TerminalNodeCount++;
return(playerNode.HeuristicValue);
}
return(playerNode.Children.Values.Max(child => this.GetPositionEvaluation(child, depth, probability)));
}
public double Evaluate(IPlayerNode node)
{
if (node.GameOver)
{
return MinEvaluation;
}
var grid = node.Grid;
var result = this.heatMaps.Select(map => EvaluateGrid(grid, map)).Max();
result -= 1 << Math.Max(0, 6 - EvaluateEmptyCells(node.Grid));
return result;
}
public double Evaluate(IPlayerNode node)
{
if (node.GameOver)
{
return(MinEvaluation);
}
var grid = node.Grid;
var result = this.heatMaps.Select(map => EvaluateGrid(grid, map)).Max();
result -= 1 << Math.Max(0, 6 - EvaluateEmptyCells(node.Grid));
return(result);
}
public static byte GetMaxValueEvalution(IPlayerNode node) => node.Grid.Flatten().Max();
public static byte GetMaxValueEvalution(IPlayerNode node) => node.Grid.Flatten().Max();
