具有创新点的六子棋开局库Q-强化学习算法C语言程序

以下是一个基于Q-强化学习算法实现的具有创新点的六子棋开局库C语言程序的示例：

#include <stdio.h>
#include <stdlib.h>
#include <time.h>

#define ROW 15
#define COL 15
#define EMPTY 0
#define BLACK 1
#define WHITE 2
#define MAXSTEP 225
#define MAXEPISODES 50000
#define ALPHA 0.1
#define GAMMA 0.9
#define EPSILON 0.1

// 定义状态结构体
typedef struct {
    int state[ROW][COL]; // 棋盘状态
    int player; // 当前玩家
} State;

// 定义动作结构体
typedef struct {
    int row;
    int col;
    int value;
} Action;

// 定义Q值结构体
typedef struct {
    double value;
    int count;
} QValue;

// 初始化状态
void initState(State *s) {
    int i, j;
    s->player = BLACK;
    for (i = 0; i < ROW; i++) {
        for (j = 0; j < COL; j++) {
            s->state[i][j] = EMPTY;
        }
    }
}

// 随机选择动作
Action selectAction(State s, QValue qTable[][COL][3], double epsilon) {
    int i, j, k;
    Action action;
    if ((double)rand() / RAND_MAX < epsilon) {
        // 随机选择动作
        do {
            action.row = rand() % ROW;
            action.col = rand() % COL;
        } while (s.state[action.row][action.col] != EMPTY);
    } else {
        // 选择最优动作
        double maxValue = -1e9;
        for (i = 0; i < ROW; i++) {
            for (j = 0; j < COL; j++) {
                if (s.state[i][j] == EMPTY) {
                    for (k = 1; k <= 2; k++) {
                        if (qTable[i][j][k].value > maxValue) {
                            maxValue = qTable[i][j][k].value;
                            action.row = i;
                            action.col = j;
                            action.value = k;
                        }
                    }
                }
            }
        }
    }
    return action;
}

// 更新Q值
void updateQValue(QValue *qValue, double reward, QValue nextQValue) {
    qValue->value += ALPHA * (reward + GAMMA * nextQValue.value - qValue->value) / (++qValue->count);
}

// 根据当前状态和策略生成下一状态
State nextState(State s, Action action) {
    State nextS = s;
    nextS.state[action.row][action.col] = action.value;
    nextS.player = 3 - s.player; // 切换玩家
    return nextS;
}

// 判断是否有五子连珠
int isWin(State s) {
    int i, j, k, m, n;
    for (i = 0; i < ROW; i++) {
        for (j = 0; j < COL; j++) {
            if (s.state[i][j] == EMPTY) {
                continue;
            }
            for (k = 0; k < 4; k++) {
                int count = 1;
                for (m = i + dx[k], n = j + dy[k]; m >= 0 && m < ROW && n >= 0 && n < COL && s.state[m][n] == s.state[i][j]; m += dx[k], n += dy[k]) {
                    count++;
                }
                for (m = i - dx[k], n = j - dy[k]; m >= 0 && m < ROW && n >= 0 && n < COL && s.state[m][n] == s.state[i][j]; m -= dx[k], n -= dy[k]) {
                    count++;
                }
                if (count >= 5) {
                    return s.state[i][j];
                }
            }
        }
    }
    return EMPTY;
}

// 六子棋Q-强化学习算法主函数
void sixChess() {
    srand((unsigned int)time(NULL)); // 随机种子
    int i, j, k, t;
    int dx[4] = {1, 0, 1, 1}; // 横向、纵向、正斜线、反斜线
    int dy[4] = {0, 1, 1, -1};
    State s;
    Action action;
    QValue qTable[ROW][COL][3]; // Q值表
    for (i = 0; i < ROW; i++) {
        for (j = 0; j < COL; j++) {
            for (k = 1; k <= 2; k++) {
                qTable[i][j][k].value = 0;
                qTable[i][j][k].count = 0;
            }
        }
    }
    for (t = 0; t < MAXEPISODES; t++) {
        initState(&s);
        for (i = 0; i < MAXSTEP; i++) {
            action = selectAction(s, qTable, EPSILON);
            State nextS = nextState(s, action);
            int winner = isWin(nextS);
            double reward;
            if (winner == s.player) {
                reward = 1;
            } else if (winner == 3 - s.player) {
                reward = -1;
            } else {
                reward = 0;
            }
            Action nextAction = selectAction(nextS, qTable, 0);
            updateQValue(&qTable[action.row][action.col][action.value], reward, qTable[nextAction.row][nextAction.col][nextAction.value]);
            if (winner != EMPTY) {
                break;
            }
            s = nextS;
        }
    }
    // 输出Q值表
    for (i = 0; i < ROW; i++) {
        for (j = 0; j < COL; j++) {
            printf("(%d,%d): ", i, j);
            for (k = 1; k <= 2; k++) {
                printf("%lf ", qTable[i][j][k].value);
            }
            printf("\n");
        }
    }
}

// 主函数
int main() {
    sixChess();
    return 0;
}

该程序实现了Q-强化学习算法，随机选择动作的策略和ε-greedy策略，并用于生成具有创新点的六子棋开局库。在程序中，Q值使用QValue结构体表示，每个状态下包含三个Q值，分别代表当前位置为空、黑色棋子、白色棋子时的Q值。程序还实现了奖励函数、更新Q值函数、下一状态生成函数、判断是否有五子连珠函数等。最后，通过输出Q值表来查看生成的具有创新点的开局库。