def feel_busy(self, board: BoardState, snake: Snake, grid_map: GridMap):
possible_actions = snake.possible_actions()
head = snake.get_head()
if possible_actions is None:
return None
actions_without_obstacle = []
for action in possible_actions:
next_field = head.advanced(action)
object_at_field = grid_map.get_value_at_position(next_field)
if board.is_out_of_bounds(next_field):
continue
if object_at_field == Occupant.Snake:
continue
actions_without_obstacle.append(action)
if len(actions_without_obstacle) > 0:
return np.random.choice(actions_without_obstacle)
else:
return None
def move(self, game_info: GameInfo, turn: int, board: BoardState, you: Snake) -> MoveResult:
possible_actions = you.possible_actions()
if possible_actions is None:
return None
grid_map = board.generate_grid_map()
busy_action = self.feel_busy(board, you, grid_map)
if busy_action is not None:
return MoveResult(direction=busy_action)
random_action = np.random.choice(possible_actions)
return MoveResult(direction=random_action)
def next_step(snake: Snake, board: BoardState, grid_map: GridMap) -> Direction:
head = snake.get_head()
#tail = snake.get_tail()
middle = Position(board.height // 2, board.width // 2)
valid = ValidActions.get_valid_actions(board, snake.possible_actions(), [snake], snake, grid_map, False)
#for direction in Direction:
# if not board.is_out_of_bounds(head.advanced(direction)):
# if not (head.advanced(direction) in snake.get_body()):
# valid.append(direction)
#if snake.get_length() > 10:
# for action in valid:
# _, path = AStar.a_star_search(head.advanced(action), tail, board, grid_map)
# print(len(path))
# end, pat = path[len(path)-1]
# if not end == tail:
# valid.remove(action)
if middle in snake.get_body():
need, next_direction = SoloSurvival.need_food(snake, board, grid_map, valid)
if need:
if next_direction in valid:
return next_direction
else:
#print("not valid")
return np.random.choice(valid)
else:
next_direction = SoloSurvival.tail_gate(snake, board, grid_map)
if next_direction in valid:
return next_direction
else:
return np.random.choice(valid)
else:
if SoloSurvival.food_around_head(head, board):
_, path = AStar.a_star_search(head, middle, board, grid_map)
_, next_direction = path[0]
else:
_, path = AStar.a_star_search(head, middle, board, grid_map)
_, next_direction = path[0]
if next_direction in valid:
return next_direction
else:
return np.random.choice(valid)
def move(self, game_info: GameInfo, turn: int, board: BoardState, you: Snake) -> MoveResult:
if you.latency:
print("Latency", you.latency)
start_time = time.time()
grid_map: GridMap[Occupant] = board.generate_grid_map()
self.Decision.set_round(turn)
next_action = self.Decision.decide(you, board, grid_map)
if not next_action:
possible_actions = you.possible_actions()
for action in possible_actions:
next_position = you.get_head().advanced(action)
for snake in board.snakes:
if next_position == snake.get_tail() and snake.health != 100:
next_action = action
if not next_action:
next_action = np.random.choice(possible_actions)
print("Move-DAUER: ", time.time() - start_time)
return MoveResult(direction=next_action)
def hunger(snake: Snake, board: BoardState, grid_map: GridMap, food_path: List[Position],
valid_actions: List[Direction], my_automat: SnakeAutomat) -> Tuple[Direction, List[Position]]:
possible_actions = snake.possible_actions()
back_up_actions = ValidActions.get_valid_actions(board, possible_actions, board.snakes, snake, grid_map, False)
if valid_actions:
action = np.random.choice(valid_actions)
else:
action = np.random.choice(back_up_actions)
if not food_path:
print(my_automat.reachable_food)
food_path = Hungry.follow_food(snake, board, grid_map, my_automat.reachable_food)
if food_path:
print("Food_Path: ", food_path)
if food_path[0][1] in valid_actions:
action = food_path[0][1]
food_path.pop(0)
else:
food_path = []
print(action)
return action, food_path
def avoid_enemy(my_snake: Snake, board: BoardState, grid_map: GridMap,
valid_actions: List[Direction], action_plan: ActionPlan,
direction_depth: Dict) -> Direction:
if not valid_actions:
possible_actions = my_snake.possible_actions()
valid_actions = ValidActions.get_valid_actions(board,
possible_actions,
board.snakes,
my_snake,
grid_map,
avoid_food=False)
num_snakes = 4 - len(board.snakes)
flood_dist = 6 if len(board.snakes) > 2 else 99
my_head = my_snake.get_head()
enemy_heads = [
snake.get_head() for snake in board.snakes
if snake.snake_id != my_snake.snake_id
]
middle = Position(int(board.height / 2), int(board.width / 2))
corners = [
Position(0, 0),
Position(0, board.width),
Position(board.height, 0),
Position(board.height, board.width)
]
escape_cost_dict = action_plan.escape_lane(my_head, valid_actions)
# TODO: Unterscheidung der Params in Late game und early game abhängig von anzahl der Schlangen
p_head = Params_Anxious.ALPHA_DISTANCE_ENEMY_HEAD[num_snakes] * (-1)
p_corner = Params_Anxious.BETA_DISTANCE_CORNERS[num_snakes]
p_mid = Params_Anxious.THETA_DISTANCE_MID[num_snakes] * (-1)
p_border = Params_Anxious.EPSILON_NO_BORDER[num_snakes]
p_food = (Params_Anxious.GAMMA_DISTANCE_FOOD[num_snakes] * 20 /
my_snake.health)
p_flood_min = Params_Anxious.OMEGA_FLOOD_FILL_MIN[num_snakes] * (-1)
p_flood_max = Params_Anxious.OMEGA_FLOOD_FILL_MAX[num_snakes]
p_flood_dead = Params_Anxious.OMEGA_FLOOD_DEAD[num_snakes]
p_corridor = Params_Anxious.RHO_ESCAPE_CORRIDOR[num_snakes] * (-1)
p_length = Params_Anxious.TAU_PATH_LENGTH[num_snakes]
total_cost = np.array([], dtype=np.float64)
direction_cost = np.zeros(10)
for action in valid_actions:
next_position = my_head.advanced(action)
# calculate flood fill
flood_fill_value, relevant_food = FloodFill.get_fill_stats(
board, next_position, my_snake.snake_id, new_pos=True)
enemy_flood = sum([
flood_fill_value[snake.snake_id] for snake in board.snakes
if snake.snake_id != my_snake.snake_id and
Distance.manhattan_dist(snake.get_head(), my_head) < flood_dist
])
# calculate all costs for heuristics
direction_cost[0] = direction_depth[action] * p_length
direction_cost[1] = escape_cost_dict[action] * p_corridor
direction_cost[2] = ActionPlan.punish_border_fields(
next_position, my_head, grid_map.width,
grid_map.height) * p_border
direction_cost[3] = sum([
Distance.manhattan_dist(next_position, enemy_head)
for enemy_head in enemy_heads
]) * p_head
direction_cost[4] = sum([
Distance.manhattan_dist(next_position, corner)
for corner in corners
if Distance.manhattan_dist(next_position, corner) < 9
]) * p_corner
direction_cost[5] = Distance.manhattan_dist(next_position,
middle) * p_mid
direction_cost[6] = flood_fill_value[
my_snake.snake_id] * p_flood_max
direction_cost[7] = enemy_flood * p_flood_min
direction_cost[8] = len(relevant_food) * p_food
# extra points for killing enemy snake
if num_snakes == 1:
enemy_id = [
snake.snake_id for snake in board.snakes
if snake.snake_id != my_snake.snake_id
][0]
if flood_fill_value[enemy_id] < 20:
flood_kill_value = (20 - flood_fill_value[enemy_id]) * 1000
direction_cost[9] = flood_kill_value * p_flood_dead
total_cost = np.append(total_cost, direction_cost.sum())
direction_cost = np.zeros(10)
if valid_actions:
best_action = valid_actions[int(np.argmax(total_cost))]
print(best_action)
else:
best_action = None
return best_action
