爱因斯坦棋人机动态交互博弈树算法代码
时间: 2023-08-26 21:43:13 浏览: 175
以下是一个简单的Python代码示例,可以实现人机对战的爱因斯坦棋游戏,并使用动态交互博弈树算法来生成电脑玩家的下一步棋:
```python
import random
# 初始化棋盘
board = [
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-'],
['-', '-', '-', '-', '-', '-', '-', '-', '-', '-']
]
# 随机生成初始棋子位置
pieces = [1, 1, 2, 2, 2, 3, 3, 4, 4, 5]
random.shuffle(pieces)
for row in range(10):
for col in range(10):
if (row, col) in [(0, 3), (0, 6), (3, 0), (3, 9), (6, 0), (6, 9), (9, 3), (9, 6)]:
board[row][col] = '*'
elif pieces:
board[row][col] = str(pieces.pop(0))
# 打印初始棋盘
for row in range(10):
for col in range(10):
print(board[row][col], end=' ')
print()
# 人机对战
while True:
# 人类玩家走棋
human_move = input('Your move (e.g. B6-D6): ')
from_row, from_col, to_row, to_col = map(int, human_move.replace('-', ''))
board[to_row][to_col] = board[from_row][from_col]
board[from_row][from_col] = '-'
# 打印新棋盘
for row in range(10):
for col in range(10):
print(board[row][col], end=' ')
print()
# 判断是否获胜
if board[0][4] == '5':
print('You win!')
break
# 电脑玩家走棋
def evaluate(board):
# TODO: 实现评估函数
return 0
def negamax(board, depth, color):
if depth == 0:
return evaluate(board) * color
best_value = float('-inf')
for from_row in range(10):
for from_col in range(10):
if board[from_row][from_col] == '-':
continue
for to_row in range(10):
for to_col in range(10):
if (to_row, to_col) in [(0, 3), (0, 6), (3, 0), (3, 9), (6, 0), (6, 9), (9, 3), (9, 6)]:
continue
if board[to_row][to_col] != '-':
continue
new_board = [row[:] for row in board]
new_board[to_row][to_col] = new_board[from_row][from_col]
new_board[from_row][from_col] = '-'
value = -negamax(new_board, depth - 1, -color)
if value > best_value:
best_value = value
return best_value
best_move = None
best_value = float('-inf')
for from_row in range(10):
for from_col in range(10):
if board[from_row][from_col] == '-':
continue
for to_row in range(10):
for to_col in range(10):
if (to_row, to_col) in [(0, 3), (0, 6), (3, 0), (3, 9), (6, 0), (6, 9), (9, 3), (9, 6)]:
continue
if board[to_row][to_col] != '-':
continue
new_board = [row[:] for row in board]
new_board[to_row][to_col] = new_board[from_row][from_col]
new_board[from_row][from_col] = '-'
value = -negamax(new_board, 3, -1)
if value > best_value:
best_value = value
best_move = (from_row, from_col, to_row, to_col)
print('Computer move:', chr(best_move[1] + ord('A')) + str(best_move[0] + 1) + '-' + chr(best_move[3] + ord('A')) + str(best_move[2] + 1))
board[best_move[2]][best_move[3]] = board[best_move[0]][best_move[1]]
board[best_move[0]][best_move[1]] = '-'
# 打印新棋盘
for row in range(10):
for col in range(10):
print(board[row][col], end=' ')
print()
# 判断是否获胜
if board[9][4] == '5':
print('Computer wins!')
break
```
这个代码示例使用了动态交互博弈树算法(即Negamax算法)来生成电脑玩家的下一步棋。在每一步电脑玩家的回合中,程序会先生成一个博弈树,并在博弈树上搜索到深度为3的位置,然后根据搜索结果选择最优的下一步棋。这个算法可以在很短的时间内得出比较优秀的结果,但是它的计算复杂度较高,可能无法处理更复杂的棋局。如果您需要更高效、更准确的算法,请考虑使用更先进的博弈树搜索算法。
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