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请教如何设计五子棋的人工智能？

zzhouj 2004-07-15 11:08:43

最近在移植和改进一个五子棋游戏，有关五子棋的人工智能，欢迎大家谈谈自己的思路。特别是喜欢玩和编写过五子棋游戏的朋友。

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thirdapple 2004-07-19

极大极小+alpha-beta剪枝

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名牌大灰狼 2004-07-19

sos http://community.csdn.net/Expert/topic/3188/3188484.xml?temp=.419552

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zzhouj 2004-07-19

重新整理一下格式：

/**
* Find best position for next step of computer player, and return the
* step score.
*/
static SINT16 FCMainFindBestPosition(SINT8 * s8SelPosX, SINT8 * s8SelPosY,
UINT8 u8ComputerPlayer,
UINT8 u8PeoplePlayer)
{
int i; /* for loop to count 5 power of u8LimitNum */

UINT8 u8PosX, u8PosY; /* for loop hole chess board */

UINT8 u8LimitNum = 0; /* for loop from five chess lint to two */
/* chess lint */

SINT16 s16Temp = 1; /* power value of 5 power of u8LimitNum */

SINT32 s32NumPosSel = 0; /* for count power of every position which */
/* is FC_NO_PALYER */

SINT32 s32MaxPosSel = 0; /* record max power of all position */

SINT32 s32Temp = 0; /* power value of */
/*FCMainFindConnectLinesByPoint() */

SINT16 s16StepScore = 0; /* return of step score */

/* initial input parameter */
*s8SelPosX = -1;
*s8SelPosY = -1;

/* from five chess lint to two chess lint */
for (u8LimitNum = 5; u8LimitNum >= 2; u8LimitNum--) {
/* loop hole chess board */
for (u8PosX = 0; u8PosX < FC_BOARD_WIDTH; u8PosX++) {
for (u8PosY = 0; u8PosY < FC_BOARD_HEIGHT; u8PosY++) {
/* only count position which is FC_NO_PALYER */
if (nFiveChessBoard[u8PosX][u8PosY] == FC_NO_PALYER) {
/* count 5 power of u8LimitNum */
s16Temp = 1;
for (i = 0; i < 5; i++) {
s16Temp = s16Temp * u8LimitNum;
}

/* first count computer player's power value */
s32Temp =
FCMainFindConnectLinesByPoint(u8PosX, u8PosY,
(UINT8)
nComputerPlayer,
u8LimitNum);
/* count power of the position */
s32NumPosSel =
(s32Temp * s16Temp + 1) * 10 +
FCMainPositionPower(u8PosX, u8PosY);
if (s32NumPosSel > s32MaxPosSel) {
s32MaxPosSel = s32NumPosSel;
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
} else if (s32NumPosSel == s32MaxPosSel) {
if ((FCPalRand() & 0x01) == 1) {
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
}

/* the count people player's power value */
s32Temp =
FCMainFindConnectLinesByPoint(u8PosX, u8PosY,
(UINT8)
nPeoplePlayer,
u8LimitNum);
s32NumPosSel =
(s32Temp * s16Temp) * 10 +
FCMainPositionPower(u8PosX, u8PosY);
if (s32NumPosSel == s32MaxPosSel) {
if ((FCPalRand() & 0x01) == 1) {
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
} else if (s32NumPosSel > s32MaxPosSel) {
s32MaxPosSel = s32NumPosSel;
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
} /* if */
} /* for */
} /* for */
} /* for */

s16StepScore = (SINT16) s32MaxPosSel;
FCPalSprintf(szGameLog, "(x, y) := (%d, %d)", *s8SelPosX, *s8SelPosY);
FCPalLogStr(szGameLog);
return s16StepScore;
}

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zzhouj 2004-07-19

各位非常感谢，但是我所面临的环境是一个资源受限的嵌入式设备，其task的堆栈很小可能只有1K，不能使用深度递归算法。不知下面的算法是否满足要求:

/**
* Find best position for next step of computer player, and return the step score.
*/
static SINT16 FCMainFindBestPosition(SINT8 * s8SelPosX, SINT8 * s8SelPosY, UINT8 u8ComputerPlayer, UINT8 u8PeoplePlayer)
{
int i; /* for loop to count 5 power of u8LimitNum */
UINT8 u8PosX, u8PosY; /* for loop hole chess board */
UINT8 u8LimitNum = 0; /* for loop from five chess lint to two chess lint */
SINT16 s16Temp = 1; /* power value of 5 power of u8LimitNum */

SINT32 s32NumPosSel = 0; /* for count power of every position which is FC_NO_PALYER */
SINT32 s32MaxPosSel = 0; /* record max power of all position */
SINT32 s32Temp = 0; /* power value of FCMainFindConnectLinesByPoint() */

SINT16 s16StepScore = 0; /* return of step score */

/* initial input parameter */
*s8SelPosX = -1;
*s8SelPosY = -1;

/* from five chess lint to two chess lint */
for (u8LimitNum = 5; u8LimitNum >= 2; u8LimitNum--) {
/* loop hole chess board */
for (u8PosX = 0; u8PosX < FC_BOARD_WIDTH; u8PosX++) {
for (u8PosY = 0; u8PosY < FC_BOARD_HEIGHT; u8PosY++) {
/* only count position which is FC_NO_PALYER */
if (nFiveChessBoard[u8PosX][u8PosY] == FC_NO_PALYER) {
/* count 5 power of u8LimitNum */
s16Temp = 1;
for (i = 0; i < 5; i++) {
s16Temp = s16Temp * u8LimitNum;
}

/* first count computer player's power value */
s32Temp = FCMainFindConnectLinesByPoint(u8PosX, u8PosY, (UINT8) nComputerPlayer, u8LimitNum);
/* count power of the position */
s32NumPosSel = (s32Temp * s16Temp + 1) * 10 + FCMainPositionPower(u8PosX, u8PosY);
if (s32NumPosSel > s32MaxPosSel) {
s32MaxPosSel = s32NumPosSel;
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
} else if (s32NumPosSel == s32MaxPosSel) {
if ((FCPalRand() & 0x01) == 1) {
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
}

/* the count people player's power value */
s32Temp = FCMainFindConnectLinesByPoint(u8PosX, u8PosY, (UINT8) nPeoplePlayer, u8LimitNum);
s32NumPosSel = (s32Temp * s16Temp) * 10 + FCMainPositionPower(u8PosX, u8PosY);
if (s32NumPosSel == s32MaxPosSel) {
if ((FCPalRand() & 0x01) == 1) {
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
} else if (s32NumPosSel > s32MaxPosSel) {
s32MaxPosSel = s32NumPosSel;
*s8SelPosX = u8PosX;
*s8SelPosY = u8PosY;
}
} /* if */
} /* for */
} /* for */
} /* for */

s16StepScore = (SINT16) s32MaxPosSel;
FCPalSprintf(szGameLog, "(x, y) := (%d, %d)", *s8SelPosX, *s8SelPosY);
FCPalLogStr(szGameLog);
return s16StepScore;
}

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shines77 2004-07-17

上面int alpha_bate(board, color, alpha, beta)
应该为 int alpha_beta(board, depth, color, alpha, beta)

下面的是int alpha_beta(board, depth, color, beta, alpha) // alpha, beta窗口必须交换

必须加入搜索深度，才知道什么时候停，但搜索GetCaptureMoves的时候例外，一般是一方GetCaptureMoves() = 0 就停止搜索，如果你实在怕搜索得太深，也可以强制加一个深度限制

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shines77 2004-07-17

没种棋都不一样，中国象棋麻烦点，因为数据结构无法利用bitboard，国际象棋是8x8的格子，稍微好处理一点，不同的棋类游戏不同的只是规则和评估函数，搜索和剪枝基本都是通用的，不过象棋的规则导致逻辑上稍微复杂一点，比如不能连续3次将军，20回合双方不吃子算和棋

象棋程序中常用静态搜索（就是假设一方不走棋，一方连续走），我想五子棋也有必要使用，象棋中有个特别的就是，搜索到最后一步，把可以对子（就是可以吃对方的棋）的棋逐一编历搜索（中间也有剪枝），这个搜索往往是不定长的，所以用了会有点慢，但对局面评估有相当大的帮助，大致结构像下面：

int alpha_bate(board, color, alpha, beta)
{
......
nMove = GetCaptureMoves(board, color, moveLists);
for(int i=0; i<nMove; i++)
{
......
alpha_bate(board, 1-color, alpha, beta);
}
......
return value;
}

其实很多算法都可以从国际象棋的代码里学到，网上国际象棋的资料比较多一些，但多数都是英文的，可以自己搜搜，我很久不看也不知道推荐什么了，基本的alpha-beta剪枝是要会的

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chenzhengzhanglu 2004-07-17

楼上的象棋应该比较难吧？

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shines77 2004-07-17

应该是alpha-beta剪枝，和局面评估函数（重点就在这，影响棋力）

剪枝可以使用Nega-Sount（常用），还有MTD(f), SS*等等Alpha-Beta的变种

哈西表也是一个较关键的应用，我没有写过五子棋的，只写过黑白棋和中国象棋，黑白棋有可以比一般剪枝搜索得更深的MPC算法（要求要有比较稳定准确的局面评估函数）

AI的关键就在评估函数这快，所以没有NowCan(((((( ★ ))))))想象的那么难，掌握了剪枝以后就是评估函数的设计了

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