象棋人工智能的实现

来源：互联网发布：excel数据粘贴到数据库编辑：程序博客网时间：2024/05/03 11:38

为了实现人机对战功能，必须实现象棋的人工智能，将象棋的每个棋子都赋予一定的权重，每走一步都计算分值，选择得分最高的一步，这是象棋人工智能的基本思想。

    #ifndef AI_H    #define AI_H    #include "cocos2d.h"    USING_NS_CC;    class SceneGame;    class Step : public CCObject    {    public:        int _moveid;        int _killid;        int _xFrom;        int _yFrom;        int _xTo;        int _yTo;        static Step* create(int moveid, int killid, int xFrom, int yFrom, int xTo, int yTo)        {            Step* step = new Step;            step->_killid = killid;            step->_moveid = moveid;            step->_xFrom = xFrom;            step->_xTo = xTo;            step->_yFrom = yFrom;            step->_yTo = yTo;            step->autorelease();            return step;        }    };    class AI    {    public:        AI(SceneGame *game);        SceneGame *_game;        Step *GenOneMove(int level=2);        int getScore();        static int _score[7];        CCArray *getAllPossibleMove();        void getAllPossibleMove(int idx,CCArray *arr);        int getMinValue(int level,int maxScore);        int getMaxValue(int level,int minScore);        Step *_step;    };    #endif // AI_H

得分表

int AI::_score[7]={    1000,    10,    10,    100,    50,    50,    20};

创建一步

Step *AI::GenOneMove(int level){    int maxScore=-10000;    Step *ret;    //find all possible access an calcute the hights score    CCArray *possibleMOve=getAllPossibleMove();    CCObject *obj;    CCARRAY_FOREACH(possibleMOve,obj)    {        Step *step=(Step*)obj;        _game->fakeMove(step);        int score=getMinValue(level-1,maxScore);        //int score=getScore();        _game->unfakeMove(step);        if(score>maxScore)        {            maxScore=score;            ret=step;        }    }    return ret;}

最大值最小值算法

int AI::getMinValue(int level,int maxScore){    if(level ==0)    {        return getScore();    }    int minScore=10000;    CCArray *possibleMOve=getAllPossibleMove();    CCObject *obj;    CCARRAY_FOREACH(possibleMOve,obj)    {        Step *step=(Step*)obj;        _game->fakeMove(step);        int score=getMaxValue(level-1,minScore);         _game->unfakeMove(step);        if(score<=maxScore)        {            minScore=score;            return minScore;        }        if(score<minScore)        {            minScore=score;        }    }    return minScore;}int AI::getMaxValue(int level,int minScore){    if(level ==0)    {        return getScore();    }    int maxScore=-10000;    CCArray *possibleMOve=getAllPossibleMove();    CCObject *obj;    CCARRAY_FOREACH(possibleMOve,obj)    {        Step *step=(Step*)obj;        _game->fakeMove(step);        int score=getMinValue(level-1,maxScore);         _game->unfakeMove(step);        if(score>=minScore)        {            maxScore=score;            break;        }        if(score>maxScore)        {            maxScore=score;        }    }    return maxScore;}

值得注意的是，象棋预先考虑的步骤越多，象棋越智能，但是当象棋考虑到第4步的时候，ubuntu就崩溃了，可以采用智能减枝算法，有效减少计算量。注意，当使用智能减枝时，一定要将假动作回移，不然会引起递归混乱。

0 0