python 围棋AI代码

下面是一个简单的围棋AI代码示例：

import numpy as np
import random

# 初始化棋盘
board_size = 9
board = np.zeros((board_size, board_size))

# 定义棋手
class Player:
    def __init__(self, stone):
        self.stone = stone

    def get_move(self, board):
        # 随机选择一个合法的落子位置
        legal_moves = self.get_legal_moves(board)
        move = random.choice(legal_moves)
        return move

    def get_legal_moves(self, board):
        legal_moves = []
        for i in range(board_size):
            for j in range(board_size):
                if board[i][j] == 0:
                    legal_moves.append((i, j))
        return legal_moves

    def make_move(self, board, move):
        board[move[0]][move[1]] = self.stone

# 创建两个棋手
player1 = Player(1)
player2 = Player(2)

# 开始对弈
current_player = player1
while True:
    move = current_player.get_move(board)
    current_player.make_move(board, move)
    print("Player", current_player.stone, "makes move:", move)
    print(board)

    # 判断游戏是否结束
    if len(player1.get_legal_moves(board)) == 0 and len(player2.get_legal_moves(board)) == 0:
        break

    # 切换棋手
    if current_player == player1:
        current_player = player2
    else:
        current_player = player1

这个示例中的围棋AI采用的是随机选择一个合法的落子位置的策略进行下棋。你可以根据需要改进AI的下棋策略，例如使用Minimax算法、蒙特卡洛树搜索等