def best_child(self, p_node):
if self.log:
print('jump')
print(p_node)
node_v_para = 2 * math.log(p_node.visited)
uct_dict = {}
for m, (c, p) in p_node.moves.items():
Q = get_max_difference(c.value, p_node.act_id) / max(c.value) if max(c.value) != 0 else 0
# N = 1 / c.visited if c.visited != 0 else MAX
N = ((node_v_para / c.visited) ** (1 / 2)) if c.visited != 0 else MAX
uct_value = Q + p + N
uct_dict[c] = uct_value
node = randomMax(uct_dict)
return node
def jump(self, node):
if self.log:
print('jump')
print(node)
node_v_para = 2 * math.log(node.visited)
uct_dict = {}
for m, (c, p) in node.moves.items():
Q = get_max_difference(c.value, self.id) / max(c.value) if max(
c.value) != 0 else 0
N = 1 / c.visited if c.visited != 0 else MAX
# N = ((node_v_para/c.visited)**(1/2)) if c.visited!=0 else MAX
uct_value = Q + p + N
uct_dict[c] = uct_value
uc_node = randomMax(uct_dict)
uc_node_v_para = 2 * math.log(
uc_node.visited) if uc_node.visited != 0 else 1
uct_dict = {}
for m, (c, p) in uc_node.moves.items():
Q = get_max_difference(c.value, self.id) / max(c.value) if max(
c.value) != 0 else 0
N = 1 / c.visited if c.visited != 0 else MAX
# N = ((uc_node_v_para/c.visited))**(1/2) if c.visited!=0 else MAX
uct_value = Q + p + N
uct_dict[c] = uct_value
if len(uct_dict) == 0:
if self.log:
print('reach the end, jump to the uc_node')
print(uc_node)
return uc_node
jump_node = randomMax(uct_dict)
if self.log:
print('normal jump to the node')
print(jump_node)
return jump_node
def search(self, moves, game_state, player_order):
self.tree = []
self.init_game_state = game_state
self.init_moves = moves
self.player_order = player_order
state = self.init_game_state
parent = None
f_move = None
act_id = self.id
root_node = Node(state, parent, f_move, act_id, self.tree)
self.root_node = root_node
self.time_monitor = defaultdict(float)
start = time.time()
n = 0
# while n<= 4:
# while True:
nodes_len = (2**(len(moves)**(1 / 2)))
while time.time() - start < len(moves) * SEARCH_TIME:
#while n<nodes_len:
#while time.time() - start < 0.2474:
#a = input('input')
n += 1
self.one_search(root_node)
print('searched times', n)
print('nodes:', len(self.tree))
print('{} finished'.format(str(self.agent.__class__)))
print('seach duration', time.time() - start)
print('distribute', self.time_monitor)
print()
dict = {}
for m, (c, p) in root_node.moves.items():
Q = get_max_difference(c.value,
self.id) if c is not None else -1000
dict[m] = Q
move = randomMax(dict)
track = self.get_predict_track(root_node, move)
if USING_GUI:
Gui(self.tree, 'mcts save')
return move
