python启发式搜索智能三子棋游戏

作为一个AI语言，Python的启发式搜索能力非常强大，非常适合用来开发智能三子棋游戏。以下是一个简单的Python启发式搜索智能三子棋游戏的示例代码：

import random
import copy

class Node:
    def __init__(self, board, player):
        self.board = board
        self.player = player
        self.children = []
        self.score = 0

    def add_child(self, node):
        self.children.append(node)

    def get_children(self):
        return self.children

    def get_score(self):
        return self.score

    def set_score(self, score):
        self.score = score

    def get_board(self):
        return self.board

    def get_player(self):
        return self.player

def create_board():
    return [[0, 0, 0], [0, 0, 0], [0, 0, 0]]

def print_board(board):
    symbols = {0: " ", 1: "X", -1: "O"}
    print("  0 1 2")
    for i in range(3):
        row = [symbols[board[i][j]] for j in range(3)]
        print("{} {}".format(i, " ".join(row)))
    print()

def get_moves(board):
    moves = []
    for i in range(3):
        for j in range(3):
            if board[i][j] == 0:
                moves.append((i, j))
    return moves

def make_move(board, move, player):
    row, col = move
    new_board = copy.deepcopy(board)
    new_board[row][col] = player
    return new_board

def has_won(board, player):
    for i in range(3):
        if board[i][0] == player and board[i][1] == player and board[i][2] == player:
            return True
        if board[0][i] == player and board[1][i] == player and board[2][i] == player:
            return True
    if board[0][0] == player and board[1][1] == player and board[2][2] == player:
        return True
    if board[0][2] == player and board[1][1] == player and board[2][0] == player:
        return True
    return False

def get_winner(board):
    if has_won(board, 1):
        return 1
    if has_won(board, -1):
        return -1
    return 0

def minimax(node, depth, alpha, beta, maximizing_player):
    if depth == 0 or len(node.get_children()) == 0:
        return node.get_score()
    if maximizing_player:
        value = -float("inf")
        for child in node.get_children():
            child_score = minimax(child, depth - 1, alpha, beta, False)
            value = max(value, child_score)
            alpha = max(alpha, value)
            if beta <= alpha:
                break
        return value
    else:
        value = float("inf")
        for child in node.get_children():
            child_score = minimax(child, depth - 1, alpha, beta, True)
            value = min(value, child_score)
            beta = min(beta, value)
            if beta <= alpha:
                break
        return value

def get_best_move(board, player):
    root = Node(board, player)
    moves = get_moves(board)
    for move in moves:
        new_board = make_move(board, move, player)
        child = Node(new_board, -player)
        root.add_child(child)
    for child in root.get_children():
        child_score = minimax(child, 3, -float("inf"), float("inf"), False)
        child.set_score(child_score)
    best_score = -float("inf")
    best_moves = []
    for child in root.get_children():
        if child.get_score() > best_score:
            best_score = child.get_score()
            best_moves = [child.get_board()]
        elif child.get_score() == best_score:
            best_moves.append(child.get_board())
    return random.choice(best_moves)

def play():
    board = create_board()
    print_board(board)
    while True:
        move_row = int(input("Enter row: "))
        move_col = int(input("Enter col: "))
        board = make_move(board, (move_row, move_col), 1)
        print_board(board)
        if has_won(board, 1):
            print("You win!")
            break
        if len(get_moves(board)) == 0:
            print("Tie!")
            break
        board = get_best_move(board, -1)
        print_board(board)
        if has_won(board, -1):
            print("Computer wins!")
            break
        if len(get_moves(board)) == 0:
            print("Tie!")
            break

play()

该代码使用了经典的极小极大算法，同时使用了alpha-beta剪枝来加速搜索过程。运行该代码可以在控制台上玩三子棋游戏，你可以先下棋，然后程序会自动下一步棋，直到游戏结束。