public static int Minimax(Board board, BoardCell targetedCell, int depth, bool maximisingPlayer)
{
Board evolvedBoard = (Board)board.Clone();
evolvedBoard.Cells[targetedCell.X][targetedCell.Y] = targetedCell;
if (depth == 0 || evolvedBoard.FreeCells == 0)
{
return(DecisionManager.Heuristic(evolvedBoard, targetedCell));
}
Polygon assessablePolygon = DecisionManager.TraceAssessablePolygon(evolvedBoard);
int bestValue;
if (maximisingPlayer)
{
bestValue = -1000;
foreach (BoardCell cell in evolvedBoard.CellList)
{
if (cell.State == BoardCell.CellState.Free && assessablePolygon.Contains(new Point {
X = cell.X, Y = cell.Y
}))
{
int result = DecisionManager.Minimax(evolvedBoard, cell, depth - 1, false);
bestValue = Math.Max(bestValue, result);
}
}
return(bestValue);
}
bestValue = 1000;
foreach (BoardCell cell in evolvedBoard.CellList)
{
if (cell.State == BoardCell.CellState.Free && assessablePolygon.Contains(new Point {
X = cell.X, Y = cell.Y
}))
{
int result = DecisionManager.Minimax(evolvedBoard, cell, depth - 1, true);
bestValue = Math.Min(bestValue, result);
}
}
return(bestValue);
}
public async Task <GameState.LastPlayed> TakeDecision(Game game)
{
if (game.GameState.Turn == 0)
{
return(new GameState.LastPlayed(9, 9));
}
GameState.LastPlayed decision = new GameState.LastPlayed(0, 0);
Polygon assessablePolygon = DecisionManager.TraceAssessablePolygon(game.Board);
foreach (BoardCell cell in game.Board.CellList)
{
if (cell.State == BoardCell.CellState.Free && assessablePolygon.Contains(new Point {
X = cell.X, Y = cell.Y
}))
{
DecisionManager.Minimax(game.Board, cell, 1, true);
}
}
return(decision);
}
public AI()
{
this._game = new Game();
this._decisionManager = new DecisionManager();
}
