我正在为 Hexapawn 开发一个 python minimax 实现，但遇到了一个问题：它打印出 ai 的正确移动，但它不会执行该移动。
这是我的代码：
import copy
class Hexapawn:
def __init__(self):
self.board = [[2,2,2],
[0,0,0],
[1,1,1]]
self.player = 1
def display_board(self):
for row in self.board:
print(row)
def ai_turn(self):
move = self.minimax(3, float('-inf'), float('inf'), True)[1]
if move:
self.make_move(move, self.board)
print("AI moves:", move)
else:
print("AI has no valid moves.")
def player_turn(self):
player_move = self.get_player_move()
self.make_move(player_move, self.board)
if self.is_game_over():
self.display_board()
print("Player wins!")
return
self.display_board()
def play_game(self):
while True:
self.player_turn()
self.player = 1 if self.player == 2 else 2
if self.is_game_over():
break
self.ai_turn()
self.player = 1 if self.player == 2 else 2
if self.is_game_over():
self.display_board()
print("AI wins!")
break
def evaluate_board(self):
player1_pawns = sum(row.count(1) for row in self.board)
player2_pawns = sum(row.count(2) for row in self.board)
return player1_pawns- player2_pawns
def get_player_move(self):
while True:
try:
orow, ocol = map(int, input("Enter row and column of the pawn you want to move (e.g., 0 1): ").split())
nrow, ncol = map(int, input("Enter row and column of the destination (e.g., 1 1): ").split())
move = ((orow, ocol), (nrow, ncol))
if move in self.get_possible_moves():
return move
else:
print("Invalid move. Try again.")
except ValueError:
print("Invalid input. Please enter row and column numbers separated by a space.")
def make_move(self, move, board):
orow,ocol = move[0]
nrow,ncol = move[1]
board[nrow][ncol] = board[orow][ocol]
board[orow][ocol] = 0
def undo_move(self, move, board):
orow, ocol = move[0]
nrow, ncol = move[1]
board[orow][ocol] = board[nrow][ncol]
board[nrow][ncol] = 0
def is_game_over(self):
if not self.get_possible_moves():
return True
for col in range(len(self.board[0])):
if self.board[0][col] == 1 or self.board[2][col] == 2:
return True
return False
def get_possible_moves(self):
possible = []
opponent=2 if self.player == 1 else 1
for row in range(len(self.board)):
for col in range(len(self.board[row])):
if self.board[row][col] == self.player:
if self.player == 1:
#diagonal
#r
if row -1 >= 0 and col +1 <= 2 and self.board[row-1][col+1] == opponent:
possible.append(((row,col),(row-1,col+1)))
#l
if row-1 >= 0 and col-1 >= 0 and self.board[row-1][col-1] == opponent:
possible.append(((row,col),(row-1,col-1)))
#vert
if row -1 >= 0 and self.board[row-1][col] == 0:
possible.append(((row,col),(row-1,col)))
elif self.player == 2:
#diag
#r
if row+1 <= 2 and col +1 <= 2 and self.board[row+1][col+1] == opponent:
possible.append(((row,col), (row+1, col+1)))
#l
if row+1 <= 2 and col -1 >= 0 and self.board[row+1][col-1] == opponent:
possible.append(((row,col),(row+1, col-1)))
#vert
if row+1 <= 2 and self.board[row+1][col] == 0:
possible.append(((row,col), (row+1, col)))
return possible
def minimax(self, depth, alpha, beta, maximizing_player):
if depth == 0 or self.is_game_over():
return self.evaluate_board(), None
board = copy.deepcopy(self.board)
if maximizing_player:
max_eval = float('-inf')
best_move = None
for move in self.get_possible_moves():
self.make_move(move, board)
evaluate = self.minimax(depth-1,alpha, beta, False)[0]
self.undo_move(move, board)
if evaluate > max_eval:
max_eval = evaluate
best_move = move
alpha = max(alpha, evaluate)
if beta <= alpha:
break
return max_eval, best_move
else:
min_eval= float('inf')
for move in self.get_possible_moves():
self.make_move(move, board)
evaluate = self.minimax(depth-1, alpha, beta, True)[0]
self.undo_move(move, board)
if evaluate<min_eval:
min_eval = evaluate
beta = min(beta, evaluate)
if beta <= alpha:
break
return min_eval, None
if __name__ == "__main__":
game = Hexapawn()
game.display_board()
game.play_game()
我试图找出为什么人工智能的举动没有反映在棋盘上，但没有成功。我错过了什么？
它打印出人工智能的正确动作，但它不会执行该动作
实际上，AI 动作已经做出了。但要真正看到结果，您应该在移动完成后立即打印棋盘：
def ai_turn(self):
move = self.minimax(3, float('-inf'), float('inf'), True)[1]
if move:
self.make_move(move, self.board)
print("AI moves:", move)
self.display_board() # <----------------- add this
else:
print("AI has no valid moves.")
上面回答了您的直接问题，但您的实现有几个问题：
在极小极大搜索期间，玩家的回合不会改变，即
self.playerget_possible_movesself.playermake_moveundo_movemaximizing_playerself.playerminimaxself.boardboardself.boardself.boardboardmake_moveself.board当游戏结束时，
evaluate该函数最大化玩家 1 的得分，但 minimax 函数是在 AI 玩家（玩家 2）作为最大化玩家的情况下调用的，因此这会影响良好的评估。
该功能不利于赢得未结束的游戏。例如，这里左边是一场获胜的比赛，右边是一场未获胜的比赛，两者的最后一步都是玩家 2 下的：
. . . . 2 .
2 1 2 1 1 .
. . . . . 2
修正第一个问题后，对于玩家 2 来说，评估函数会倾向于左侧的棋盘，因为它的棋盘比对手的棋子多，但右侧的棋盘显然更好，因为它是一个棋盘。赢。要么首先检测胜利并为此类棋盘提供优先分数，要么为棋盘上更先进的棋子提供更多分数。