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 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
