def init_deck(self):
suits = ['黑桃', '红桃', '梅花', '方块']
values = ['2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K', 'A']
for suit in suits:
for value in values:
self.deck.append(Card(value, suit))
random.shuffle(self.deck)
def deal_cards(self):
for _ in range(17):
for player in self.players:
player.draw([self.deck.pop(0)])
剩余三张牌作为底牌,给地主
bottom_cards = [self.deck.pop(0) for _ in range(3)]
self.players[0].draw(bottom_cards)
def play(self):
self.deal_cards()
for player in self.players:
print(f{player.name}'s hand: {len(player.hand)} cards)
game = Game()
game.play()
简单AI决策
这个AI只会随机出牌。创建一个更复杂的AI需要更详细的游戏树、策略评估函数和可能的机器学习模型。
python
class SimpleAI(Player):
def decide(self, last_played=None):
if not self.hand:
return None
简单策略:随机出一张牌
return random.choice(self.hand)
更新Player类以支持AI决策
class AIPlayer(Player):
def __init__(self, name):
super().__init__(name)