def update_turn(board, player, node, network, pos):
"""
take board, player number, current node, player network and opponent move
return child node according to opponent move
"""
# get child from number of empty moves before opponent move
complete_board = (board[:, :, 0] + board[:, :, 1]).flatten()
child = node.get_child(
np.sum((complete_board[:(pos[1] * 19 + pos[0])] == 0)))
# if unexplored yet
if child.leaf():
expand(child, board, player, network)
return child
def init_game(network_1, network_2):
"""
init game board, first node, next player turn
"""
board = init_map()
# board = np.zeros((19, 19, 3), np.int8)
# player 1
node_p_1 = Node(0)
expand(node_p_1, board, 0, network_1)
# player 2
node_p_2 = Node(0)
expand(node_p_2, board, 1, network_2)
return board, node_p_1, node_p_2
def test_winning_move_when_one():
"""
test if network find winning move among one
return true if winning move is found
return else otherwise
"""
while True:
has_winning_move = 0
tmp = np.random.randint(3, size=(19, 19))
board = np.zeros((1, 19, 19, 3), dtype=int)
for y in range(19):
for x in range(19):
if tmp[y, x] == 1:
board[0, y, x, 0] = 1
if evaluate(board, 0, [y, x]):
board[0, y, x, 0] = 0
if has_winning_move:
has_winning_move = 1
elif tmp[y, x] == 2:
board[0, y, x, 1] = 1
if evaluate(board, 1, [y, x]):
board[0, y, x, 1] = 0
if has_winning_move:
has_winning_move = 2
if not has_winning_move:
continue
network = Network(0)
node = Node(0)
expand(node, board, has_winning_move - 1, network)
turn(board, has_winning_move - 1, node, network)
for y in range(19):
for x in range(19):
if evaluate(board, has_winning_move - 1, [y, x]):
return True
return False
def basic_win():
"""
test with simple env
"""
e = np.array([[0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
board = conv_map(e)
player = 1
root = Node(0)
net = Network(-1)
expand(root, board, player, net)
p, _ = net.infer(board)
print_policy(board, p[0])
pos, n_board, p, p_node, status = mcts(board, player, root, net)
print_policy(board, p)
#root.debug()
#print (pos)
#print(evaluate(board, player, pos))
return 1
required=True)
parser.add_argument('-v', help='Network version', required=True)
parser.add_argument('-d',
help='1 or 0, Outputs network policy, and mcts policy',
required=True)
args = vars(parser.parse_args())
player = int(args["s"]) - 1
version = int(args["v"])
debug = int(args["d"])
board = np.zeros((19, 19, 3), np.int8)
node = Node(0)
net = Network(version)
expand(node, board, player, net)
if player == 0:
node, _ = human_turn(board, node, player, net)
# game
r = 0
while (not r):
# ia
if debug:
p, _ = net.infer(board)
_, board, p_, node, r = mcts(board, player ^ 1, node, net)
if debug:
print("Network policy:")
def play_turn(board, player, network):
print("DEBUG", "Calculating the next move")
node = Node(0)
expand(node, board, player, network)
(x, y), _, _, _, _ = mcts(board, player, node, network)
print("%d,%d" % (int(x), int(y)))
