通过Python实现——A*算法 (附上代码+详细解释)
时间: 2023-07-20 08:23:02 浏览: 62
好的,以下是 Python 实现 A* 算法的代码:
```python
from queue import PriorityQueue
class State:
def __init__(self, value, parent, start=0, goal=0):
self.children = []
self.parent = parent
self.value = value
self.distance = 0
if parent:
self.start = parent.start
self.goal = parent.goal
self.path = parent.path[:]
self.path.append(value)
else:
self.start = start
self.goal = goal
self.path = [value]
def get_distance(self):
pass
def create_children(self):
pass
class State_String(State):
def __init__(self, value, parent, start=0, goal=0):
super().__init__(value, parent, start, goal)
self.distance = self.get_distance()
def get_distance(self):
if self.value == self.goal:
return 0
distance = 0
for i in range(len(self.goal)):
letter = self.goal[i]
distance += abs(i - self.value.index(letter))
return distance
def create_children(self):
if not self.children:
for i in range(len(self.goal) - 1):
val = self.value
val = val[:i] + val[i+1] + val[i] + val[i+2:]
child = State_String(val, self)
self.children.append(child)
class AStar_Solver:
def __init__(self, start, goal):
self.path = []
self.visited_queue = []
self.priority_queue = PriorityQueue()
self.start = start
self.goal = goal
def solve(self):
start_state = State_String(self.start, None, self.start, self.goal)
count = 0
self.priority_queue.put((0, count, start_state))
while not self.path and self.priority_queue.qsize():
closest_child = self.priority_queue.get()[2]
closest_child.create_children()
self.visited_queue.append(closest_child.value)
for child in closest_child.children:
if child.value not in self.visited_queue:
count += 1
if not child.distance:
self.path = child.path
break
self.priority_queue.put((child.distance, count, child))
if not self.path:
print("Goal of " + self.goal + " is not possible!")
return self.path
start = "dabcfehg"
goal = "abcdefgh"
a = AStar_Solver(start, goal)
a.solve()
print(a.path)
```
在上述代码中,`State` 类表示状态,包含当前状态值、父状态、起始状态、目标状态、路径和距离等属性。`State_String` 类是 `State` 类的子类,用于处理字符串类型的状态。`get_distance` 函数用于计算当前状态与目标状态之间的距离,`create_children` 函数用于创建当前状态的子状态。
`AStar_Solver` 类是 A* 算法的主要实现部分。在 `__init__` 函数中,我们初始化路径和队列等属性。在 `solve` 函数中,我们首先将起始状态加入优先队列,并不断从队列中取出距离最短的状态,生成其子状态,并将未访问过的子状态加入优先队列中。在每次加入子状态到队列中时,我们使用 `count` 属性来确保优先队列中的元素是按照加入顺序排序的。当找到目标状态时,我们提取路径并返回。
最后,我们通过调用 `AStar_Solver` 类来解决字符串类型的问题。在此例中,我们使用字符串 "dabcfehg" 作为起始状态,使用字符串 "abcdefgh" 作为目标状态。
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