def get_action(self, board: BoardInfo) -> (int, int):
self.get_alert(board)
self.action_number = self.action_number + 1
self.state.update_with_board_info(board)
maxtime = 2
if self.action_number == 1:
maxtime = 5
move = UCT(rootstate=self.state, maxtime=maxtime, verbose=False)
print("Best Move: " + str(move))
possible_x = int(move / self.state.n)
possible_y = int(move % self.state.n)
if board.is_legal_action(possible_x, possible_y):
print("Move possible: %d,%d" % (possible_x, possible_y))
return possible_x, possible_y
else:
print("Move not possible: %d,%d" % (possible_x, possible_y))
# default to easy ai for now, need another solution
for x in range(0, board.size_x):
for y in range(0, board.size_y):
if board.is_legal_action(x, y):
return x, y
else:
continue
def get_action(self, board: BoardInfo):
possible_actions = self.get_possible_actions(board)
weighted_actions = self.get_weighted_actions(board, possible_actions)
for ((x, y), _) in weighted_actions:
if board.is_legal_action(x, y):
return x, y
return 5, 5
def get_possible_actions(board: BoardInfo):
possible_actions = set()
for ((x, y), _) in board.steps:
for (dx, dy) in [(1, 0), (-1, 0), (0, 1), (0, -1), (1, 1), (-1, -1), (-1, 1), (1, -1)]:
if board.is_legal_action(x + dx, y + dy):
possible_actions.add((x + dx, y + dy))
return possible_actions
def get_action(self, board: BoardInfo, timeout):
possible_actions = self.get_possible_actions(board)
weighted_actions = self.get_weighted_actions(board, possible_actions)
for ((x, y), _) in weighted_actions:
#print(board.steps[:])
if board.is_legal_action(x, y):
return x, y
return 5, 5
def get_action(self, board: BoardInfo) -> (int, int):
"""
Implement your algorithm here.
**Important**
1. You must return (x, y)
2. If any exception is raised, you will lose the game directly. Use try-except to handle error/exception.
3. To get current state of the game, you could call board.dense or board.steps to get data.
:return: int x, int y
"""
for x in range(0, board.size_x):
for y in range(0, board.size_y):
if board.is_legal_action(x, y):
return x, y
else:
continue
def get_critical_actions(self, board: BoardInfo):
deffensive_actions = []
winning_actions = []
for ((x, y), _) in board.steps:
for (dx, dy) in [(1, 0), (-1, 0), (0, 1), (0, -1), (1, 1),
(-1, -1), (-1, 1), (1, -1)]:
if board.is_legal_action(x + dx, y + dy):
weight = analysis_action(board, (x + dx, y + dy),
self.color)
if weight >= 100:
deffensive_actions.append(((x + dx, y + dy), weight))
if weight <= -1:
winning_actions.append(((x + dx, y + dy), weight))
deffensive_actions = sorted(deffensive_actions,
key=lambda x: x[1],
reverse=True)
return deffensive_actions, winning_actions