public static int ComputerVSComputer(EvaluateFunction fun1, EvaluateFunction fun2)
{
// 经过指定步数则为和棋
int step = Settings.DRAW_STEPS;
GameState gs = new GameState();
ChessPiece winner = ChessPiece.EMPTY;
while (step-- != 0)
{
winner = gs.WhoIsWin();
if (winner == ChessPiece.EMPTY)
{
if (step == Settings.DRAW_STEPS - 1)
{
gs.PlaceChessInCenter();
Debug.WriteLine("{0} {1} {2}", gs.X, gs.Y, GameState.AnotherPlayer(gs.turn).ToString());
}
else if (step % 2 == 1)
{
PlaceChessAI(gs, fun1);
Debug.WriteLine("{0} {1} {2}", gs.X, gs.Y, GameState.AnotherPlayer(gs.turn).ToString());
}
else if (step % 2 == 0)
{
PlaceChessAI(gs, fun2);
Debug.WriteLine("{0} {1} {2}", gs.X, gs.Y, GameState.AnotherPlayer(gs.turn).ToString());
}
}
else if (winner == ChessPiece.CROSS)
{
return(Settings.WIN_FITNESS);
}
else if (winner == ChessPiece.NOUGHT)
{
return(Settings.LOSE_FITNESS);
}
}
return(Settings.DRAW_FITNESS);
}
/// <summary>
/// MIN_MAX博弈的核心
/// </summary>
/// <param name="gs">游戏状态</param>
/// <param name="depth">搜素深度</param>
/// <param name="min">允许的最小值</param>
/// <param name="max">允许的最大值</param>
/// <param name="cp">评判的是哪一方</param>
/// <param name="ef">可调整的评价函数</param>
/// <returns></returns>
public static double MinMax(GameState gs, int depth, double min, double max, ChessPiece cp, EvaluateFunction ef)
{
ChessPiece winner = gs.WhoIsWin();
if (winner == cp)
{
return(Settings.WIN_POINT);
}
else if (winner == GameState.AnotherPlayer(cp))
{
return(Settings.LOSE_POINT);
}
if (depth == 0)
{
return(ef(gs));
}
double value, temp_value;
// 当前为极大节点
if (gs.NextPlayer() == cp)
{
// 检查其所有子节点
value = min;
IEnumerator <GameState> ie_gs = gs.GetNextSiblingStates();
while (ie_gs.MoveNext())
{
if (IsNessarySearch(ie_gs.Current, ie_gs.Current.X, ie_gs.Current.Y))
{
temp_value = MinMax(ie_gs.Current, depth - 1, value, max, cp, ef);
// alpha pruning
if (temp_value > value)
{
value = temp_value;
}
if (value > max)
{
return(max);
}
}
}
return(value);
}
// 当前为极小节点
else
{
// 检查其所有子节点
value = max;
IEnumerator <GameState> ie_gs = gs.GetNextSiblingStates();
while (ie_gs.MoveNext())
{
if (IsNessarySearch(ie_gs.Current, ie_gs.Current.X,
ie_gs.Current.Y))
{
// beta pruning
temp_value = MinMax(ie_gs.Current, depth - 1, min, value, cp, ef);
if (temp_value < value)
{
value = temp_value;
}
if (value < min)
{
return(min);
}
}
}
return(value);
}
}
