def a_star(successors, start_state, goal_test, heuristic=lambda s: 0, alpha=0):
if goal_test(start_state):
return [start_state]
agenda = PriorityQueue()
agenda.push(SearchNode(start_state, None, cost=0),
alpha * heuristic(start_state))
expanded = set()
while len(agenda) > 0:
priority, parent = agenda.pop()
if parent.state not in expanded:
expanded.add(parent.state)
if goal_test(parent.state):
print(str(len(expanded)) + ",")
#print("Cost of path: " + str(path_cost(parent.path())))
return parent.path()
for child_state, cost in successors(parent.state):
child = SearchNode(child_state, parent, parent.cost + cost)
if child_state not in expanded:
agenda.push(child, (1 - alpha) * child.cost +
alpha * heuristic(child_state))
return None
def uniform_cost_search(successors,
start_state,
goal_test,
heuristic=lambda s: 0):
if goal_test(start_state):
return [start_state]
agenda = PriorityQueue()
agenda.push(SearchNode(start_state, None, cost=0), heuristic(start_state))
expanded = set()
while len(agenda) > 0:
priority, parent = agenda.pop()
if parent.state not in expanded:
expanded.add(parent.state)
if goal_test(parent.state):
print("Number of expanded states: " + str(len(expanded)))
print("Cost of path: " + str(path_cost(parent.path())))
return parent.path()
for child_state, cost in successors(parent.state):
child = SearchNode(child_state, parent, parent.cost + cost)
if child_state not in expanded:
agenda.push(child, child.cost + heuristic(child_state))
return None
def __init__(self, state, parent, cost):
SearchNode.__init__(self, state)
self.parent = parent
self.cost = cost
def __init__(self, state, parent):
SearchNode.__init__(self, state)
self.parent = parent
def __init__(self, state, parent, cost):
SearchNode.__init__(self, state)
self.parent = parent
self.cost = cost