def create_possibilites(self, node):
"""
Gets a list of possible new moves, makes sure they are not already in the list, applies heurstic and adds them
:type node: (int, Flow)
"""
new_states = utils.generate_possible_moves_single_gp(node[1])
for new_state in new_states:
if new_state not in [new_node[1] for new_node in self.frontier]:
# New cost is the cost of the heuristic, plus the cost of the parent node, plus 1.
cost = (self.heuristic(new_state) + node[0] + 1)
self.frontier.append((cost, new_state))
def create_possibilites(self, node):
"""
Gets a list of possible new moves, makes sure they are not already in the list, applies heurstic and adds them
:type node: (int, Flow)
"""
new_states = utils.generate_possible_moves_single_gp(node[1])
for new_state in new_states:
if new_state not in [new_node[1] for new_node in self.frontier]:
# New cost is the cost of the heuristic, plus the cost of the parent node, plus 1.
cost = (self.heuristic(new_state) + node[0] + 1)
self.frontier.append((cost, new_state))
def solve(self, initial_game_state):
"""
:type initial_game_state: Flow
:return Flow:
"""
self.queue.put((astar().heuristic(initial_game_state), initial_game_state))
current_cost = 0
while self.queue._qsize() > 0:
pop = self.queue.get()
game = pop[1]
current_cost += pop[0]
# print current_cost
if utils.at_goal(game):
return game
possible_moves = utils.generate_possible_moves_single_gp(game)
for i, value in enumerate(possible_moves):
# print possible_moves[i]
self.queue.put((astar().heuristic(possible_moves[i]) + current_cost, possible_moves[i]))
return None
def solve(self, initial_game_state):
"""
:type initial_game_state: Flow
:return Flow:
"""
self.queue.put(
(astar().heuristic(initial_game_state), initial_game_state))
current_cost = 0
while self.queue._qsize() > 0:
pop = self.queue.get()
game = pop[1]
current_cost += pop[0]
# print current_cost
if utils.at_goal(game):
return game
possible_moves = utils.generate_possible_moves_single_gp(game)
for i, value in enumerate(possible_moves):
# print possible_moves[i]
self.queue.put(
(astar().heuristic(possible_moves[i]) + current_cost,
possible_moves[i]))
return None
