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())
"""
"*** YOUR CODE HERE ***"
from util import Stack
nodes = Stack()
closed = dict()
moves = list()
for var in problem.getSuccessors(problem.getStartState()):
state = FringeState(var[0])
state.moves.append(Directions.convToDirection(var[1]))
nodes.push(state)
closed[problem.getStartState()] = True
while(False == nodes.isEmpty()):
current_node = nodes.pop()
#print "Current node:", current_node
if(closed.has_key(current_node.pos)):
continue
if(problem.isGoalState(current_node.pos)):
print "Goal reached!"
moves = current_node.moves
break
for var in problem.getSuccessors(current_node.pos):
state = FringeState(var[0])
state.moves= copy.deepcopy(current_node.moves)
state.moves.append(Directions.convToDirection(var[1]))
nodes.push(state)
closed[current_node.pos] = True
return moves
def uniformCostSearch(problem):
"""Search the node of least total cost first."""
from util import PriorityQueue
nodes = PriorityQueue()
closed = dict()
moves = list()
for var in problem.getSuccessors(problem.getStartState()):
state = FringeState(var[0])
state.moves.append(Directions.convToDirection(var[1]))
state.cost = var[2]
nodes.push(state, state.cost)
closed[problem.getStartState()] = True
while(False == nodes.isEmpty()):
current_node = nodes.pop()
#print "Current node:", current_node
if(closed.has_key(current_node.pos)):
continue
if(problem.isGoalState(current_node.pos)):
print "Goal reached!"
moves = current_node.moves
break
for var in problem.getSuccessors(current_node.pos):
state = FringeState(var[0])
state.moves= copy.deepcopy(current_node.moves)
state.moves.append(Directions.convToDirection(var[1]))
state.cost = var[2] + current_node.cost
nodes.push(state, state.cost)
closed[current_node.pos] = True
return moves
def aStarSearch(problem, heuristic=nullHeuristic):
"""Search the node that has the lowest combined cost and heuristic first."""
from util import PriorityQueue
nodes = PriorityQueue()
closed = dict()
moves = list()
for var in problem.getSuccessors(problem.getStartState()):
state = FringeState(var[0])
state.moves.append(Directions.convToDirection(var[1]))
state.cost = var[2]
nodes.push(state, state.cost + heuristic(state.pos,problem))
closed[problem.getStartState()] = True
while(False == nodes.isEmpty()):
current_node = nodes.pop()
#print "Current node:", current_node
if(closed.has_key(current_node.pos)):
continue
if(problem.isGoalState(current_node.pos)):
print "Goal reached!"
moves = current_node.moves
break
for var in problem.getSuccessors(current_node.pos):
state = FringeState(var[0])
state.moves= copy.deepcopy(current_node.moves)
state.moves.append(Directions.convToDirection(var[1]))
state.cost = var[2] + current_node.cost
nodes.push(state, state.cost + heuristic(state.pos,problem))
closed[current_node.pos] = True
return moves
def breadthFirstSearch(problem):
"""Search the shallowest nodes in the search tree first."""
"*** YOUR CODE HERE ***"
from util import Queue
nodes = Queue()
closed = dict()
moves = list()
for var in problem.getSuccessors(problem.getStartState()):
state = FringeState(var[0])
state.moves.append(Directions.convToDirection(var[1]))
nodes.push(state)
closed[problem.getStartState()] = True
while(False == nodes.isEmpty()):
current_node = nodes.pop()
#print "Current node:", current_node
if(closed.has_key(current_node.pos)):
continue
if(problem.isGoalState(current_node.pos)):
print "Goal reached!"
moves = current_node.moves
break
for var in problem.getSuccessors(current_node.pos):
state = FringeState(var[0])
state.moves= copy.deepcopy(current_node.moves)
state.moves.append(Directions.convToDirection(var[1]))
nodes.push(state)
closed[current_node.pos] = True
return moves
