def find_next_food(snake: Snake, board: BoardState) -> Optional[Tuple[int, Position]]:
head = snake.get_head()
health = snake.get_health()
all_food = board.food
if len(all_food) == 0:
print("KEIN FOOD")
return None
best_dist = 99999
best_food = None
for food in all_food:
food_dist = Distance.manhattan_dist(head, food)
if food_dist > health:
continue
#print("food_dist: ",food_dist, "health", health)
if food_dist == health:
# print("1: ", food_dist, food)
return food_dist, food
else:
diff = (health - food_dist)
#print("diff: ",diff)
if (best_dist > diff) and diff > 0:
best_dist = diff
best_food = food
#print("2: ", best_dist, best_food)
return best_dist, best_food
def best_food_around_body(snake: Snake, board: BoardState) -> Tuple[int, Optional[Position]]:
length = snake.get_length()
health = snake.get_health()
body = snake.get_body()
foods = [] #Tuple[int, Position]
position = 0
any_f = False
for part in body:
for direction in Direction:
if board.is_occupied_by_food(part.advanced(direction)):
diff = length - position
add = diff, part
foods.append(add)
any_f = True
position += 1
best_dist = 999999
best_food = None
if any_f:
for dist, food in foods:
if (dist == snake.get_length()) and (health <= 1):
return 1, food
if dist < best_dist and dist <= health:
if dist == health:
return dist, food
best_dist = dist
best_food = food
return best_dist, best_food
else:
return 0, None
def parse_snake(json):
snake_id = json['id']
snake_name = json['name']
# kilab specific attribute
snake_color = json['color'] if 'color' in json else None
health = json['health']
body_json_list = json['body']
latency = json['latency'] if 'latency' in json else 0
# head = json['head']
# length = json['length']
shout = json['shout'] if 'shout' in json else ""
squad = json['squad'] if 'squad' in json else ""
body = Importer.parse_position_array(body_json_list)
snake = Snake(
snake_id=snake_id,
snake_name=snake_name,
snake_color=snake_color,
health=health,
body=body,
latency=latency,
shout=shout,
squad=squad,
)
if "elimination_event" in json:
e = json["elimination_event"]
if e is not None:
event = EliminationEvent(EliminatedCause(e["cause"]),
e["turn"], e["by"])
snake.elimination_event = event
return snake
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 snake_has_lost_head_to_head(self, s: Snake, other: Snake):
head = s.get_head()
other_head = other.get_head()
if head.x == other_head.x and head.y == other_head.y:
return len(s.body) <= len(other.body)
return False
def direction_to_food(snake: Snake, food: Position) -> Optional[Direction]:
head = snake.get_head()
for direction in Direction:
if head.advanced(direction) == food:
return direction
return None
def get_relevant_food(my_snake: Snake, snakes: List[Snake],
all_food: List[Position], height: int,
width: int) -> List[Position]:
my_head = my_snake.get_head()
enemy_heads = [
snake.get_head() for snake in snakes
if snake.get_head() is not my_head
]
my_close_food = []
for food in all_food:
if food.x == 0 or food.y == 0 or food.x == width - 1 or food.y == height - 1:
enemy_dist_to_me = min([
Distance.manhattan_dist(head, my_head)
for head in enemy_heads
])
enemy_dist_to_food = min([
Distance.manhattan_dist(head, food) for head in enemy_heads
])
if len(all_food) > 5 and my_snake.health > 50:
continue
if my_snake.health > 25 and enemy_dist_to_food < 2:
continue
if my_snake.health > 70 and enemy_dist_to_food < 2 and enemy_dist_to_me < 2:
continue
my_close_food.append(food)
if not my_close_food:
my_close_food = all_food
return my_close_food
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 snake_is_out_of_bounds(self, s: Snake, board_width: int, board_height: int):
head = s.get_head()
if head.x < 0 or head.x >= board_width:
return True
elif head.y < 0 or head.y >= board_height:
return True
return False
def snake_has_body_collided(self, s: Snake, other: Snake):
head = s.get_head()
for i, body in enumerate(other.body):
if i == 0:
continue
elif body.x == head.x and body.y == head.y:
return True
return False
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 create_initial_board_state(self, width: int, height: int, snake_ids: List[str]):
board: BoardState = BoardState(width=width, height=height)
for snake_id in snake_ids:
board.add_snake(Snake(snake_id=snake_id))
self.place_snakes(board)
self.place_food(board)
return board
def get_valid_actions(board: BoardState, possible_actions: List[Direction],
snakes: List[Snake], my_snake: Snake,
grid_map: GridMap[Occupant],
avoid_food: bool) -> List[Direction]:
my_head = my_snake.get_head()
snake_tails = []
val_actions = []
forbidden_fields = []
for snake in snakes:
if snake.snake_id != my_snake.snake_id:
for direc in snake.possible_actions():
enemy_head = snake.get_head()
forbidden_fields.append(enemy_head.advanced(direc))
if snake.health == 100:
continue
snake_tails.append(snake.get_tail())
for direction in possible_actions:
next_position = my_head.advanced(direction)
# avoid eating
if my_snake.health > Params_ValidActions.FOOD_BOUNDARY and avoid_food and my_snake.get_length(
) > 5:
if grid_map.get_value_at_position(
next_position) is Occupant.Food:
continue
# outofbounds
if board.is_out_of_bounds(next_position):
continue
# body crash -> ganze Gegner Schlange minus letzten Teil
if grid_map.get_value_at_position(
next_position
) is Occupant.Snake and next_position not in snake_tails:
continue
# if next_position in forbidden_fields:
# continue
val_actions.append(direction)
if not val_actions:
for direction in possible_actions:
next_position = my_head.advanced(direction)
# eat if its the only possible valid action
if grid_map.get_value_at_position(
next_position) is Occupant.Food:
val_actions.append(direction)
return val_actions
def test_clone(self):
snake_a = Snake(snake_id="snake-a", body=[Position(x=3, y=3)])
snake_b = Snake(snake_id="snake-a", body=[Position(x=9, y=9)])
food_a = Food(x=1, y=2)
snakes = [snake_a, snake_b]
food = [food_a]
board = BoardState(width=15, height=15, snakes=snakes, food=food)
board_clone = board.clone()
self.assertNotEqual(id(board), id(board_clone))
self.assertNotEqual(id(board.snakes[0]), id(board_clone.snakes[0]))
self.assertNotEqual(id(board.food[0]), id(board_clone.food[0]))
board_export = board.to_json()
board_clone_export = board_clone.to_json()
self.assertEqual(board_export, board_clone_export)
def tail_gate(snake: Snake, board: BoardState, grid_map : GridMap) -> Direction:
head = snake.get_head()
tail = snake.get_tail()
body = snake.get_body()
distance = Distance.manhattan_dist(head, tail)
if distance == 1:
for direction in Direction:
if head.advanced(direction) == tail:
return direction
else:
dist = 9999
next_direction = None
for direction in Direction:
advanced_head = head.advanced(direction)
d = Distance.manhattan_dist(advanced_head, tail)
if advanced_head not in body:
if d < dist:
dist = d
next_direction = direction
return next_direction
def flood_kill(enemy: Snake, my_snake: Snake, kill_board: np.ndarray,
board: BoardState, grid_map: GridMap):
# TODO: Parameter snake_dead_in_rounds um mehr valide actions zu erhalten
# - breite des PFades auf 1 begrenzen
my_head = my_snake.get_head()
enemy_head = enemy.get_head()
kill_actions = []
search = False
for part in enemy.body:
kill_board[part.x][part.y] -= 1000
kill_board[my_head.x][my_head.y] -= 1000
x, y = np.unravel_index(kill_board.argmax(), kill_board.shape)
print(kill_board)
print(Position(x, y))
for (pos_x, pos_y) in get_valid_neigbours(x, y, kill_board):
if 0 > kill_board[pos_x][pos_y] > -800:
x, y = pos_x, pos_y
search = True
break
enemy_dist = Distance.manhattan_dist(enemy_head, Position(x, y))
my_dist = Distance.manhattan_dist(my_head, Position(x, y))
if enemy_dist > my_dist and search:
cost, path = AStar.a_star_search(my_head, Position(x, y), board,
grid_map)
count = 0
for pos, dir in path:
if kill_board[pos.x][pos.y] >= 0:
return []
kill_actions.append(dir)
count += 1
return kill_actions
def need_food(snake: Snake, board: BoardState, grid_map: GridMap, valid: List[Direction]) -> Tuple[bool, Optional[Direction]]:
health = snake.get_health()
head = snake.get_head()
food_around = SoloSurvival.food_all_around_body(snake, board)
if health < 15:
if food_around:
if health == 1:
_, food_pos = SoloSurvival.best_food_around_body(snake, board)
food_dir = SoloSurvival.direction_to_food(snake, food_pos)
return True, food_dir
else:
dist, food_pos = SoloSurvival.find_next_food(snake, board)
#direction, path = Hungry.hunger(snake, board, grid_map, [], valid, SnakeAutomat(snake, False))
#food_dir = SoloSurvival.direction_to_food(snake, food_pos)
#print("head: ", head, " food: ", food_pos)
_, path_ = AStar.a_star_search(head, food_pos, board, grid_map)
_, path = path_[0]
#print("path: ",path)
#food_dir = SoloSurvival.direction_to_food(snake, path[0])
return True, path
#print("hungry health: ", health)
dist, food_pos = SoloSurvival.best_food_around_body(snake, board)
if food_pos is None:
dist, food_pos = SoloSurvival.find_next_food(snake, board)
if (health - dist) <= 1:
#print("get the perfect food")
food_dir = SoloSurvival.direction_to_food(snake, food_pos)
return True, food_dir
else:
#print("anderes food nehmen")
dist, food_pos = SoloSurvival.find_next_food(snake, board)
if dist <= health:
food_dir = SoloSurvival.direction_to_food(snake, food_pos)
return True, food_dir
else:
return False, 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 test_to_json(self):
snake_a = Snake(snake_id="snake-a", body=[Position(x=3, y=3)])
snake_b = Snake(snake_id="snake-a", body=[Position(x=9, y=9)])
food_a = Food(x=1, y=2)
hazard_a = Hazard(x=4, y=1)
snakes = [snake_a, snake_b]
food = [food_a]
hazards = [hazard_a]
board = BoardState(width=15,
height=20,
snakes=snakes,
food=food,
hazards=hazards)
json_data = board.to_json()
self.assertEqual(json_data['width'], 15)
self.assertEqual(json_data['height'], 20)
self.assertListEqual(json_data['food'], [{'x': 1, 'y': 2}])
self.assertListEqual(json_data['hazards'], [{'x': 4, 'y': 1}])
def food_all_around_body(snake: Snake, board: BoardState) -> bool:
body = snake.get_body()
food_next_to_body = 0
for part in body:
thispart = False
for direction in Direction:
if board.is_occupied_by_food(part.advanced(direction)):
thispart = True
if thispart:
food_next_to_body += 1
if food_next_to_body == len(body):
return True
else:
return False
def follow_food(snake: Snake, board: BoardState, grid_map: GridMap, reachable_food: List[Position]) \
-> List[Tuple[Position, Direction]]:
my_head = snake.get_head()
food = None
relevant_foods = RelevantFood.get_relevant_food(snake, board.snakes, reachable_food, board.width, board.height)
if not relevant_foods:
return []
start_distance = 99
# get food that is nearest to my head
for relevant_food in relevant_foods:
distance = Distance.manhattan_dist(my_head, relevant_food)
if distance < start_distance:
food = relevant_food
start_distance = distance
print("best food:", food)
if not food or start_distance > 15:
return []
cost, path = AStar.a_star_search(my_head, food, board, grid_map)
path_array = path
return path_array
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
def feed_snake(self, snake: Snake):
self.grow_snake(snake)
snake.health = self.snake_max_health
def grow_snake(self, snake: Snake):
if len(snake.body) > 0:
tail = snake.get_tail()
snake.body.append(tail)
