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 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