python极小极大值搜索智能三子棋游戏实验内容

三子棋是一种非常简单的棋类游戏，其规则为两个玩家轮流在一个 $3\times 3$ 的棋盘上放置棋子，先将三个棋子连成一线的玩家获胜。极小极大值搜索是一种常用的博弈树搜索算法，可以用于解决类似于三子棋这样的博弈问题。

下面是一个使用 Python 实现极小极大值搜索智能三子棋游戏的实验内容：

1. 首先定义棋盘类和棋子类，以及棋盘的初始化操作。

class ChessBoard:
    def __init__(self):
        self.board = [[' ' for _ in range(3)] for _ in range(3)]
        self.player = 'X'
        self.winner = None

    def display(self):
        print('   0   1   2')
        print('0  ' + ' | '.join(self.board[0]))
        print('  -----------')
        print('1  ' + ' | '.join(self.board[1]))
        print('  -----------')
        print('2  ' + ' | '.join(self.board[2]))

    def move(self, x, y):
        if self.board[x][y] == ' ':
            self.board[x][y] = self.player
            if self.check_win():
                self.winner = self.player
            if self.player == 'X':
                self.player = 'O'
            else:
                self.player = 'X'
            return True
        else:
            return False

    def check_win(self):
        for i in range(3):
            if self.board[i][0] == self.board[i][1] == self.board[i][2] != ' ':
                return True
            if self.board[0][i] == self.board[1][i] == self.board[2][i] != ' ':
                return True
        if self.board[0][0] == self.board[1][1] == self.board[2][2] != ' ':
            return True
        if self.board[0][2] == self.board[1][1] == self.board[2][0] != ' ':
            return True
        return False

    def get_valid_moves(self):
        moves = []
        for i in range(3):
            for j in range(3):
                if self.board[i][j] == ' ':
                    moves.append((i, j))
        return moves


class ChessPiece:
    def __init__(self, x, y, player):
        self.x = x
        self.y = y
        self.player = player

2. 然后定义极小极大值搜索算法的实现，其中 `max_value` 和 `min_value` 分别代表极大值和极小值的计算函数。

def max_value(state):
    if state.winner is not None:
        if state.winner == 'X':
            return 1
        else:
            return -1
    v = float('-inf')
    for move in state.get_valid_moves():
        next_state = deepcopy(state)
        next_state.move(*move)
        v = max(v, min_value(next_state))
    return v


def min_value(state):
    if state.winner is not None:
        if state.winner == 'X':
            return 1
        else:
            return -1
    v = float('inf')
    for move in state.get_valid_moves():
        next_state = deepcopy(state)
        next_state.move(*move)
        v = min(v, max_value(next_state))
    return v


def minimax_search(state):
    best_move = None
    best_value = float('-inf')
    for move in state.get_valid_moves():
        next_state = deepcopy(state)
        next_state.move(*move)
        v = min_value(next_state)
        if v > best_value:
            best_move = move
            best_value = v
    return best_move

3. 最后是主函数，实现了人类玩家和 AI 玩家的交互。

def main():
    chess_board = ChessBoard()
    while True:
        chess_board.display()
        if chess_board.winner is not None:
            print('Winner:', chess_board.winner)
            break
        if chess_board.player == 'X':
            x = int(input('X: Enter row: '))
            y = int(input('X: Enter column: '))
            if not chess_board.move(x, y):
                print('Invalid move!')
        else:
            move = minimax_search(chess_board)
            chess_board.move(*move)

以上就是使用 Python 实现极小极大值搜索智能三子棋游戏的全部内容。