AI人工智能 构建一个玩井字棋游戏的机器人
井字棋是一个非常熟悉且最受欢迎的游戏之一。让我们使用 Python 中的 easyAI 库来创建这个游戏。以下代码是这个游戏的 Python 代码:
导入所需的包,如下所示:
from easyAI import TwoPlayersGame, AI_Player, Negamax
from easyAI.Player import Human_Player
从 TwoPlayerGame 类继承这个类,以处理游戏的所有操作:
class TicTacToe_game(TwoPlayersGame):
def __init__(self, players):
现在,定义玩家和将要开始游戏的玩家:
self.players = players
self.nplayer = 1
定义棋盘的类型:
self.board = [0] * 9
现在,有一些特定的事情需要定义,如下所示:
定义可能的移动:
def possible_moves(self):
return [x + 1 for x, y in enumerate(self.board) if y == 0]
定义玩家的移动:
def make_move(self, move):
self.board[int(move) - 1] = self.nplayer
为了增强 AI,定义玩家何时进行移动:
def umake_move(self, move):
self.board[int(move) - 1] = 0
定义失败条件,即对手有三个连成一线:
def condition_for_lose(self):
possible_combinations = [[1,2,3], [4,5,6], [7,8,9],
[1,4,7], [2,5,8], [3,6,9], [1,5,9], [3,5,7]]
return any([all([(self.board[z-1] == self.nopponent)
for z in combination]) for combination in possible_combinations])
定义游戏结束的检查:
def is_over(self):
return (self.possible_moves() == []) or self.condition_for_lose()
显示游戏中玩家的当前位置:
def show(self):
print('\n'+'\n'.join([' '.join([['.', 'O', 'X'][self.board[3*j + i]]
for i in range(3)]) for j in range(3)]))
计算分数:
def scoring(self):
return -100 if self.condition_for_lose() else 0
定义主方法来定义算法并开始游戏:
if __name__ == "__main__":
algo = Negamax(7)
TicTacToe_game([Human_Player(), AI_Player(algo)]).play()
你可以看到以下输出和这个游戏的简单玩法:
. . .
. . .
. . .
Player 1 what do you play ? 1
Move #1: player 1 plays 1 :
O . .
. . .
. . .
Move #2: player 2 plays 5 :
O . .
. X .
. . .
Player 1 what do you play ? 3
Move #3: player 1 plays 3 :
O . O
. X .
. . .
Move #4: player 2 plays 2 :
O X O
. X .
. . .
Player 1 what do you play ? 4
Move #5: player 1 plays 4 :
O X O
O X .
. . .
Move #6: player 2 plays 8 :
O X O
O X .
. X .