def dfs(level):
smap = level.smap
first_node = Node(level.start, None, [])
stack = []
#metemos al nodo inicial en la cola
stack.append(first_node)
processed = set()
nodes_processed = 0
# mientras que la cola tenga elementos y no gane
won = False
while stack and not won:
# saco el primer nodo del stack
node = stack.pop()
# print('ITERATION: ', nodes_processed, ' --------------------------------------------------------------')
# print("Current node: ", node.config)
# agrego este nodo a los nodos procesados
processed.add(node.config)
# primero me fijo si gane
if(finished(node.config.boxes, level)):
# si gane listo
# print("Found solution!")
won = True
else:
nodes_processed += 1
# si no gane pido mis movimientos legales
possible_configs = next_configs(node.config, level.smap)
# print("Possible configs: ", possible_configs)
children = node.children
#por cada movimiento legal me fijo si ya tube esta config antes y si no la apendeo a la cola
# print("Procesed: ===>", processed)
for config in possible_configs.difference(processed):
# print("Config: +++>", config)
# print("Was not in processed")
new_node = Node(copy.copy(config), node, [])
children.append(new_node)
stack.append(new_node)
# print("Added move: ", new_node.config)
# print("Used configs: ", processed)
# print("Stack is: ", stack)
if won:
path = build_path(node)
return process_results(won, smap, node, path, ALGORITHM_NAME, nodes_processed - 1, len(stack))
else:
return process_results(won, smap, None, [], ALGORITHM_NAME, nodes_processed - 1, len(stack))
def bfs(level):
smap = level.smap
first_node = Node(level.start, None, [])
queue = []
#metemos al nodo inicial en la cola
queue.append(first_node)
processed = set()
nodes_processed = 0
# mientras que la cola tenga elementos y no gane
won = False
while queue and not won:
# saco el primer nodo de la cola
node = queue.pop(0)
# print("Current node: ", node.config)
# agrego este nodo a los nodos procesados
processed.add(node.config)
# primero me fijo si gane
if(finished(node.config.boxes, level)):
# si gane listo
print("Found solution!")
won = True
else:
nodes_processed += 1
# si no gane pido mis movimientos legales
possible_configs = next_configs(node.config, level.smap)
# print("Possible configs: ", possible_configs)
children = node.children
#por cada movimiento legal me fijo si ya tube esta config antes y si no la apendeo a la cola
for config in possible_configs.difference(processed):
new_node = Node(copy.copy(config), node, [])
children.append(new_node)
queue.append(new_node)
# print("Added move: ", new_node.config)
# print("Used configs: ", processed)
# print("Queue is: ", queue)
if won:
path = build_path(node)
return process_results(won, smap, node, path, ALGORITHM_NAME, nodes_processed - 1, len(queue))
else:
return process_results(won, smap, None, [], ALGORITHM_NAME, nodes_processed - 1, len(queue))
def idastar(level, heu, testall):
h=heu["func"]
initial_time = datetime.now()
smap = level.smap
first_node = Node(level.start, None, [], 0, {'g': 0, 'h': h(smap, level.goals, level.start)})
lim = first_node.meta['g'] + first_node.meta['h'] # f(n0)
min_exceeded_lim = -1
def cp(e1, e2):
g1 = e1.meta['g']
g2 = e2.meta['g']
h1 = e1.meta['h']
h2 = e2.meta['h']
f1 = g1 + h1
f2 = g2 + h2
if f1 == f2:
return h1 - h2
else:
return f1 - f2
q1 = []
q2 = []
out_of_frontier = OrderedList(cp)
q1.append(first_node)
known_nodes = HashTable()
known_nodes.put(first_node.config, first_node)
nodes_processed = 0
won = False
first_found = False
while (q1 or q2) and not won:
if not q1:
q1 = q2
q2 = []
lim = min_exceeded_lim
min_exceeded_lim = -1
node = q1.pop()
f = node.meta['g'] + node.meta['h']
if f > lim:
q2.append(node)
continue
if(finished(node.config.boxes, level)):
won = True
else:
nodes_processed += 1
possible_configs = next_configs(node.config, level.smap)
children = node.children
for config in possible_configs:
proc_node = known_nodes.get(config)
if proc_node and node.depth + 1 >= proc_node.depth:
continue
new_node = Node(copy.copy(config), node, [], node.depth + 1, {'g': node.depth + 1, 'h': h(smap, level.goals, config)})
known_nodes.put(config, new_node)
children.append(new_node)
f = new_node.meta['g'] + new_node.meta['h']
if f > lim:
q2.append(new_node)
if min_exceeded_lim == -1 or f < min_exceeded_lim:
min_exceeded_lim = f
else:
q1.append(new_node)
finish_time = datetime.now()
elapsed_time = finish_time - initial_time
if won:
path = build_path(node)
return process_results(won, testall, elapsed_time, smap, node, path, f"{ALGORITHM_NAME} ({heu['name']})", nodes_processed - 1, len(q1) + len(q2))
else:
return process_results(won, testall, elapsed_time, smap, None, [], f"{ALGORITHM_NAME} ({heu['name']})", nodes_processed - 1, len(q1) + len(q2))
def astar(level, heu, testall):
h = heu["func"]
initial_time = datetime.now()
smap = level.smap
first_node = Node(level.start, None, [], 0, {
'g': 0,
'h': h(smap, level.goals, level.start)
})
def cp(e1, e2):
g1 = e1.meta['g']
g2 = e2.meta['g']
h1 = e1.meta['h']
h2 = e2.meta['h']
f1 = g1 + h1
f2 = g2 + h2
if f1 == f2:
return h1 - h2
else:
return f1 - f2
nodes_list = OrderedList(cp)
nodes_list.add(first_node)
#known_cfgs = set()
known_nodes = HashTable()
#known_cfgs.add(first_node.config)
known_nodes.put(first_node.config, first_node)
nodes_processed = 0
won = False
while nodes_list.length() > 0 and not won:
node = nodes_list.pop()
if (finished(node.config.boxes, level)):
won = True
else:
nodes_processed += 1
possible_configs = next_configs(node.config, level.smap)
children = node.children
for config in possible_configs:
proc_node = known_nodes.get(config)
new_node = Node(copy.copy(config), node, [], node.depth + 1, {
'g': node.depth + 1,
'h': h(smap, level.goals, config)
})
if proc_node:
new_node_f = new_node.meta['g'] + new_node.meta['h']
proc_node_f = proc_node.meta['g'] + proc_node.meta['h']
if (new_node_f >= proc_node_f):
continue
# if config in known_cfgs:
# continue
#known_cfgs.add(config)
known_nodes.put(config, new_node)
children.append(new_node)
nodes_list.add(new_node)
finish_time = datetime.now()
elapsed_time = finish_time - initial_time
if won:
path = build_path(node)
return process_results(won, testall, elapsed_time, smap, node, path,
f"{ALGORITHM_NAME} ({heu['name']})",
nodes_processed - 1, nodes_list.length())
else:
return process_results(won, testall, elapsed_time, smap, None, [],
f"{ALGORITHM_NAME} ({heu['name']})",
nodes_processed - 1, nodes_list.length())
def ggs(level, heu, testall):
h = heu["func"]
initial_time = datetime.now()
smap = level.smap
first_node = Node(level.start, None, [], 0,
{'h': h(smap, level.goals, level.start)})
def cp(e1, e2):
return e1.meta['h'] - e2.meta['h']
nodes_list = OrderedList(cp)
#metemos al nodo inicial en la cola ( ͡° ͜ʖ ͡°)
nodes_list.add(first_node)
known_cfgs = set()
known_cfgs.add(first_node.config)
nodes_processed = 0
# mientras que la cola tenga elementos y no gane
won = False
while nodes_list.length() > 0 and not won:
# saco el primer nodo del nodes_list
node = nodes_list.pop()
# print('ITERATION: ', nodes_processed, ' --------------------------------------------------------------')
# print("Current node: ", node.config)
# primero me fijo si gane
if (finished(node.config.boxes, level)):
# si gane listo
# print("Found solution!")
won = True
else:
nodes_processed += 1
# si no gane pido mis movimientos legales
possible_configs = next_configs(node.config, level.smap)
# print("Possible configs: ", possible_configs)
children = node.children
#por cada movimiento legal me fijo si ya tube esta config antes y si no la apendeo a la cola
# print("Procesed: ===>", processed)
for config in possible_configs:
if config in known_cfgs:
continue
known_cfgs.add(config)
new_node = Node(copy.copy(config), node, [], node.depth + 1,
{'h': h(smap, level.goals, config)})
children.append(new_node)
nodes_list.add(new_node)
# print("Added move: ", new_node.config)
# print("Used configs: ", processed)
# print("Stack is: ", stack)
finish_time = datetime.now()
elapsed_time = finish_time - initial_time
if won:
path = build_path(node)
return process_results(won, testall, elapsed_time, smap, node, path,
f"{ALGORITHM_NAME} ({heu['name']})",
nodes_processed - 1, nodes_list.length())
else:
return process_results(won, testall, elapsed_time, smap, None, [],
f"{ALGORITHM_NAME} ({heu['name']})",
nodes_processed - 1, nodes_list.length())