在showBord(bord:list)实现棋盘状态可视化、is_goal_state(state,goal_state)实现棋盘状态判断,find_zero(state)、is_valid(state)、move(state,direction)、move_sequence(state,sequence)实现规则允许下的棋盘操作,这些基础上编程实现宽度优先搜索算法
时间: 2023-09-14 20:05:56 浏览: 41
好的,让我来逐一回答你的问题。
首先,关于棋盘状态可视化,你可以在程序中定义一个函数 `showBoard(bord:list)`,该函数可以将棋盘状态 `bord` 以可视化的形式输出。你可以使用类似于以下的代码实现:
```python
def showBoard(bord: list):
for i in range(len(bord)):
for j in range(len(bord[i])):
print(bord[i][j], end=" ")
print()
```
然后,关于棋盘状态判断,你可以在程序中定义一个函数 `is_goal_state(state, goal_state)`,该函数可以判断当前状态 `state` 是否为目标状态 `goal_state`。你可以使用类似于以下的代码实现:
```python
def is_goal_state(state, goal_state):
return state == goal_state
```
接下来,关于棋盘操作,我们可以定义以下几个函数:
1. `find_zero(state)`:该函数可以用于查找当前状态 `state` 中的空白格子,即值为 0 的格子。你可以使用类似于以下的代码实现:
```python
def find_zero(state):
for i in range(len(state)):
for j in range(len(state[i])):
if state[i][j] == 0:
return i, j
```
2. `is_valid(state)`:该函数可以用于判断当前状态 `state` 是否合法,即是否存在规则允许的操作。你可以使用类似于以下的代码实现:
```python
def is_valid(state):
zero_i, zero_j = find_zero(state)
return (zero_i > 0) or (zero_i < len(state) - 1) or (zero_j > 0) or (zero_j < len(state[0]) - 1)
```
3. `move(state, direction)`:该函数可以用于根据给定的方向 `direction`,在当前状态 `state` 中移动空白格子。你可以使用类似于以下的代码实现:
```python
def move(state, direction):
zero_i, zero_j = find_zero(state)
if direction == "up":
state[zero_i][zero_j], state[zero_i-1][zero_j] = state[zero_i-1][zero_j], state[zero_i][zero_j]
elif direction == "down":
state[zero_i][zero_j], state[zero_i+1][zero_j] = state[zero_i+1][zero_j], state[zero_i][zero_j]
elif direction == "left":
state[zero_i][zero_j], state[zero_i][zero_j-1] = state[zero_i][zero_j-1], state[zero_i][zero_j]
elif direction == "right":
state[zero_i][zero_j], state[zero_i][zero_j+1] = state[zero_i][zero_j+1], state[zero_i][zero_j]
return state
```
4. `move_sequence(state, sequence)`:该函数可以用于根据给定的操作序列 `sequence`,依次在当前状态 `state` 中移动空白格子。你可以使用类似于以下的代码实现:
```python
def move_sequence(state, sequence):
for direction in sequence:
state = move(state, direction)
return state
```
最后,关于宽度优先搜索算法,你可以使用以下代码实现:
```python
from collections import deque
def bfs(start_state, goal_state):
queue = deque([(start_state, [])])
visited = set()
while queue:
state, path = queue.popleft()
if is_goal_state(state, goal_state):
return path
if str(state) in visited:
continue
visited.add(str(state))
if is_valid(state):
for direction in ["up", "down", "left", "right"]:
new_state = move(state, direction)
if str(new_state) not in visited:
queue.append((new_state, path + [direction]))
return None
```
以上就是实现宽度优先搜索算法的全部内容。当然,这只是一个简单的实现,你可以根据自己的需要进行修改和优化。