def depthFirstSearch(problem):
"""
Search the deepest nodes in the search tree first.
Your search algorithm needs to return a list of actions that reaches the
goal. Make sure to implement a graph search algorithm.
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())
"""
#Initialize the frontier using the initial state of the problem
node = Node((problem.getStartState(), 'None', 0), None)
if problem.isGoalState(node.state):
return node.getPath()
frontier = util.Stack()
frontier.push(node)
#Initialize the explored set to be empty
explored = set()
while True:
if frontier.isEmpty():
print "Failure!"
break
#Choose a leaf node and remove it from the frontier
node = frontier.pop()
if problem.isGoalState(node.state):
return node.getPath()
#If the node contains a goal state, return the solution
#if problem.isGoalState(node.state):
#return node.getPath()
#Add the state of the node to the explored set
explored.add(node.state)
#Expand the chosen node
successors = problem.getSuccessors(node.state)
for succ in successors:
child = Node(succ, node)
if child.state not in explored and child not in frontier.list:
frontier.push(child)
print "Solution not found!"
util.raiseNotDefined()
def breadthFirstSearch(problem):
"""Search the shallowest nodes in the search tree first."""
node = Node((problem.getStartState(), 'None', 0), None)
if problem.isGoalState(node.state):
return node.getPath()
#A FIFO queue with node as the only element
frontier = util.Queue()
frontier.push(node)
#An empty set
explored = set()
while True:
if frontier.isEmpty():
break
node = frontier.pop()
if problem.isGoalState(node.state):
return node.getPath()
#Add node's state to explored
explored.add(node.state)
successors = problem.getSuccessors(node.state)
for succ in successors:
child = Node(succ, node)
if (child.state not in explored) and (child not in frontier.list):
frontier.push(child)
explored.add(child.state)
print "Failure!"
return None
def uniformCostSearch(problem):
"""Search the node of least total cost first."""
node = Node((problem.getStartState(), "None", 0), None)
if problem.isGoalState(node.state):
return node.getPath()
frontier = util.PriorityQueue()
frontier.push(node, node.pathCost)
explored = set()
while True:
if frontier.isEmpty():
break
#Object of class Node
node = frontier.pop()
if problem.isGoalState(node.state):
return node.getPath()
if node.state not in explored:
successors = problem.getSuccessors(node.state)
for succ in successors:
child = Node(succ, node)
if (child.state not in explored) and (child
not in frontier.heap):
frontier.update(child, child.pathCost)
explored.add(node.state)
print "Failure!"
return None
def aStarSearch(problem, heuristic=nullHeuristic):
"""Search the node that has the lowest combined cost and heuristic first."""
#actions = path
node = node = Node((problem.getStartState(), "None", 0), None)
frontier = util.PriorityQueue()
frontier.push(node, heuristic(node.state, problem))
explored = set()
while True:
if frontier.isEmpty():
break
node = frontier.pop()
#if problem.isGoalState(node.state):
#return node.getPath()
explored.add(node.state)
successors = problem.getSuccessors(node.state)
for succ in successors:
child = Node(succ, node)
if (child.state not in explored) and (child not in frontier.heap):
if problem.isGoalState(child.state):
return child.getPath()
frontier.push(child,
child.pathCost + heuristic(child.state, problem))
elif child in frontier.heap:
frontier.update(
child, child.pathCost + heuristic(child.state, problem))
print "Failure!"
return None
