def a_star_search(graph, start, goal):
searchFrontier = PriorityQueue()
searchFrontier.put(start, heuristic[start])
currentCost = {}
currentCost[start] = 0
path = ""
while not searchFrontier.empty():
current = searchFrontier.get()
# add node in path
path += current + " "
if current == goal:
break
for next in graph.neighbors(current):
newCost = currentCost[current] + weights[(current, next)]
if next not in currentCost or newCost < currentCost[next]:
currentCost[next] = newCost
priority = newCost + heuristic[next] # set priority
searchFrontier.put(next,
priority) # add node in priority queue
return path
def main():
selection = int(sys.argv[1])
# Reads in the board from the random_board.py output
board = list(map(int, sys.stdin.read().split()))
board = [[board[0], board[1], board[2]], [board[3], board[4], board[5]],
[board[6], board[7], board[8]]]
state = State(board)
# Setting the x and y position for the blank tile
for i in range(0, 3):
for j in range(0, 3):
if board[i][j] == 0:
state.setx(i)
state.sety(j)
# Initialize the relevent data structures
curr_node = Node(state, h(state, selection))
closed = Set()
frontier = PriorityQueue()
frontier.push(curr_node)
V = 0
# Loops through and creates the search tree
while objective(curr_node.getstate()) == False:
closed.add(curr_node.getstate())
# Creates new states based on the valid_moves returned by the successor
for valid_state in successor(curr_node.getstate()):
V += 1
# Checking that the state we are eveluating has not already been expanded. Only adds to the queue if false
if closed.isMember(valid_state) == False:
frontier.push(
Node(valid_state, h(valid_state, selection), curr_node))
curr_node = frontier.pop()
N = closed.length() + frontier.length()
d = curr_node.getd()
print("V=%d" % (V))
print("N=%d" % (N))
print("d=%d" % (d))
print("b=%f" % (N**(1 / d)))
print()
# Create an empty list in order to retrieve the path from the goal node's parents
stack = []
while curr_node.getid() != 0:
stack.append(curr_node)
curr_node = curr_node.getparent()
print(curr_node.getstate())
# Prints out the solution path
for node in reversed(stack):
if node != None:
print(node.getstate())
def bestfs(graph, start, goal):
searchFrontier = PriorityQueue()
searchFrontier.put(start, heuristic[start])
predecessor = {}
predecessor[start] = None
path = ""
while not searchFrontier.empty():
current = searchFrontier.get()
path += current + " "
if current == goal:
break
for next in graph.neighbors(current):
if next not in predecessor:
priority = heuristic[next]
searchFrontier.put(next, priority)
predecessor[next] = current
return path