def solve(self, solving_cube, time_limit=None, iter_limit=None):
if time_limit is None and iter_limit is None:
raise ValueError('infinite loop maybe')
if iter_limit is None:
iter_limit = ITER_LIMIT
solving_cube = solving_cube.copy()
start_time = time.time()
actions = []
for i_current in range(iter_limit):
state = cube.get_state(solving_cube)
observation = cube.get_observation(state)
if cube.is_done(state):
return True, actions, i_current, None
action = cube.ACTIONS[self.policy.select_action(observation)]
actions.append(action)
solving_cube.perform_step(action)
if time_limit and time.time() - start_time > time_limit:
return False, None, i_current, None
else:
return False, None, iter_limit, None
def update(self):
if self.is_leaf:
if self.is_done:
return True, [], self.depth
self.probabilities = self.mcts.policy.get_action_probabilities(
cube.get_observation(cube.get_state(self.cube)),
self.mcts.temperature)
if DEBUG:
print('node is leaf, init all children')
print('probs: {}'.format(' '.join(list(map(
lambda x: str(round(x, 2)),
self.probabilities.probs.numpy())))))
self.is_leaf = False
return False, None, self.depth
else:
action = self.probabilities.sample()
if DEBUG:
print('depth = {}\tnext action = {}'.format(
self.depth, cube.ACTIONS[action]))
if self.children[action] is None:
self.children[action] = SimpleNode(
self.cube.copy().perform_step(cube.ACTIONS[action]),
self.mcts, self.depth + 1)
is_done, actions, max_depth = self.children[action].update()
if is_done:
return True, [cube.ACTIONS[action]] + actions, max_depth
else:
return False, None, max_depth
def __init__(self, node_cube, mcts, depth):
self.cube = node_cube
self.mcts = mcts
self.depth = depth
self.is_leaf = True
self.is_done = cube.is_done(cube.get_state(node_cube))
self.probabilities = None
self.children = [None] * cube.N_ACTION
def __init__(self, node_cube, mcts, depth, c_puct):
self.cube = node_cube
self.mcts = mcts
self.depth = depth
self.c_puct = c_puct
self.state = cube.get_state(node_cube)
self.is_done = cube.is_done(self.state)
self.sum_value = float(self.mcts.value_f.get_value(self.state))
self.count_value = 1
self.visit_count = 0
self.is_leaf = True
self.probabilities = None
self.children = [None] * cube.N_ACTION