为了好玩，我正在 berkley 网站的 AI 类(class)页面上找到一项作业。我需要为 pacman 游戏编写深度优先搜索，以便它可以找到它的路径。问题是 pacman 卡住了。我将首先粘贴代码以使我说的更清楚:
import util
class SearchProblem:
"""
This class outlines the structure of a search problem, but doesn't implement
any of the methods (in object-oriented terminology: an abstract class).
You do not need to change anything in this class, ever.
"""
def getStartState(self):
"""
Returns the start state for the search problem
"""
util.raiseNotDefined()
def isGoalState(self, state):
"""
state: Search state
Returns True if and only if the state is a valid goal state
"""
util.raiseNotDefined()
def getSuccessors(self, state):
"""
state: Search state
For a given state, this should return a list of triples,
(successor, action, stepCost), where 'successor' is a
successor to the current state, 'action' is the action
required to get there, and 'stepCost' is the incremental
cost of expanding to that successor
"""
util.raiseNotDefined()
def getCostOfActions(self, actions):
"""
actions: A list of actions to take
This method returns the total cost of a particular sequence of actions. The sequence must
be composed of legal moves
"""
util.raiseNotDefined()
def tinyMazeSearch(problem):
"""
Returns a sequence of moves that solves tinyMaze. For any other
maze, the sequence of moves will be incorrect, so only use this for tinyMaze
"""
from game import Directions
s = Directions.SOUTH
w = Directions.WEST
return [s,s,w,s,w,w,s,w]
def depthFirstSearch(problem):
"""
Search the deepest nodes in the search tree first [p 74].
Your search algorithm needs to return a list of actions that reaches
the goal. Make sure to implement a graph search algorithm [Fig. 3.18].
To get started, you might want to try some of these simple commands to
understand the search problem that is being passed in:
print 'Start:', problem.getStartState()
print 'Is the start a goal?', problem.isGoalState(problem.getStartState())
print 'Start's successors:', problem.getSuccessors(problem.getStartState())
"""
# *** YOUR CODE HERE ***
start = [problem.getStartState()]
for item in start:
Open=[item]
State=[]
Closed=[]
Path=[]
if problem.isGoalState(Open[0]) is True:
return State
else:
while Open:
visit= Open.pop()
Closed.append(visit)
if State:
Path.append(State.pop())
if problem.isGoalState(visit) is True:
print Closed
return Path
else:
Successors= problem.getSuccessors(visit)
for index in Successors:
it=iter(index)
data=it.next()
if data not in Closed :
Open.append(data)
State.append(it.next())
else:
print Path
现在，如果您在 dfs 下阅读我的代码，您会看到 open 列表包含我访问和扩展的所有点。
Path 文件包含为 pacman 设置的方向。当我遇到我得到的两个后继者都未被访问的情况时，问题就出现了，我的 pacman 走了一条通往死胡同的路径，所以它需要回溯。我的 Open 做到了并找到了解决方案，但我无法找到如何在我的路径列表中提供回溯方向的方法。如果你要去http://inst.eecs.berkeley.edu/~cs188/sp09/projects/search/search.html并下载 zip 并将我的代码粘贴到 dfs 搜索下的 search.py 中，您将了解我的问题。
请您参考如下方法:
一些提示:
- 您检查的每个节点都应该封装您如何到达那里的数据。
- DFS 就像一个堆栈；您首先按下启动状态。您弹出堆栈，然后推回可以跟随您弹出的节点的节点。
- 由于您最终要尝试找到一条路径，因此节点数据必须包含您的位置以及您到达那里所采用的路径。
